In [23]:
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
C:\Users\razerblade 15\AppData\Roaming\Python\Python39\site-packages\matplotlib\projections\__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.
  warnings.warn("Unable to import Axes3D. This may be due to multiple versions of "
In [2]:
unemployment=pd.read_csv("Unemployement_rate.csv")
unemployment
Out[2]:
Date Actual Forecast Previous
0 5-Apr-24 3.80% 3.90% 3.90%
1 8-Mar-24 3.90% 3.70% 3.70%
2 2-Feb-24 3.70% 3.80% 3.70%
3 5-Jan-24 3.70% 3.80% 3.70%
4 8-Dec-23 3.70% 3.90% 3.90%
... ... ... ... ...
71 4-May-18 3.90% 4.00% 4.10%
72 6-Apr-18 4.10% 4.00% 4.10%
73 9-Mar-18 4.10% 4.00% 4.10%
74 2-Feb-18 4.10% 4.10% 4.10%
75 5-Jan-18 4.10% 4.10% 4.10%

76 rows × 4 columns

In [16]:
unemployment.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 76 entries, 0 to 75
Data columns (total 4 columns):
 #   Column                 Non-Null Count  Dtype         
---  ------                 --------------  -----         
 0   Date                   76 non-null     datetime64[ns]
 1   unemployment_Actual    76 non-null     object        
 2   unemployment_Forecast  76 non-null     object        
 3   unemployment_Previous  76 non-null     object        
dtypes: datetime64[ns](1), object(3)
memory usage: 2.5+ KB
In [17]:
IWM=pd.read_csv("IWM.csv")
IWM
Out[17]:
Date Open High Low Close Adj Close Volume
0 1/2/2018 153.199997 153.970001 152.460007 153.899994 141.990631 20489600
1 1/3/2018 153.869995 154.460007 153.520004 154.059998 142.138260 21836600
2 1/4/2018 154.970001 155.149994 154.020004 154.470001 142.516525 14207100
3 1/5/2018 154.880005 154.979996 153.940002 154.789993 142.811752 19883900
4 1/8/2018 154.729996 155.270004 153.500000 155.029999 143.033173 18457300
... ... ... ... ... ... ... ...
1580 4/15/2024 199.369995 200.229996 194.979996 195.779999 195.779999 41119300
1581 4/16/2024 194.410004 196.240005 193.360001 195.059998 195.059998 43267500
1582 4/17/2024 196.470001 196.619995 192.990005 193.000000 193.000000 38589500
1583 4/18/2024 193.699997 195.660004 192.149994 192.839996 192.839996 40238200
1584 4/19/2024 191.940002 194.389999 191.339996 193.139999 193.139999 42499200

1585 rows × 7 columns

In [18]:
QQQ=pd.read_csv("QQQ.csv")
QQQ
Out[18]:
Date Open High Low Close Adj Close Volume
0 1/2/2018 156.559998 158.529999 156.169998 158.490005 151.871933 32573300
1 1/3/2018 158.639999 160.169998 158.610001 160.029999 153.347641 29383600
2 1/4/2018 160.580002 160.789993 160.080002 160.309998 153.615906 24776100
3 1/5/2018 161.070007 162.029999 160.770004 161.919998 155.158768 26992300
4 1/8/2018 161.919998 162.630005 161.860001 162.550003 155.762390 23159100
... ... ... ... ... ... ... ...
1580 4/15/2024 442.059998 442.149994 430.209991 431.059998 431.059998 63453600
1581 4/16/2024 430.899994 433.760010 429.700012 431.100006 431.100006 47619000
1582 4/17/2024 433.100006 433.119995 424.899994 425.839996 425.839996 56880500
1583 4/18/2024 426.489990 428.239990 422.829987 423.410004 423.410004 46549400
1584 4/19/2024 422.220001 422.750000 413.070007 414.649994 414.649994 75136600

1585 rows × 7 columns

In [19]:
SPY=pd.read_csv("SPY.csv")
SPY
Out[19]:
Date Open High Low Close Adj Close Volume
0 1/2/2018 267.839996 268.809998 267.399994 268.769989 242.319351 86655700
1 1/3/2018 268.959991 270.640015 268.959991 270.470001 243.852097 90070400
2 1/4/2018 271.200012 272.160004 270.540009 271.609985 244.879929 80636400
3 1/5/2018 272.510010 273.559998 271.950012 273.420013 246.511826 83524000
4 1/8/2018 273.309998 274.100006 272.980011 273.920013 246.962494 57319200
... ... ... ... ... ... ... ...
1580 4/15/2024 515.130005 515.299988 503.579987 504.450012 504.450012 92101400
1581 4/16/2024 504.940002 506.500000 502.209991 503.529999 503.529999 73484000
1582 4/17/2024 506.049988 506.220001 499.119995 500.549988 500.549988 75910300
1583 4/18/2024 501.980011 504.130005 498.559998 499.519989 499.519989 74548100
1584 4/19/2024 499.440002 500.459991 493.859985 495.160004 495.160004 102129100

1585 rows × 7 columns

In [28]:
SPY['Date'] = pd.to_datetime(SPY['Date'])
QQQ['Date'] = pd.to_datetime(SPY['Date'])
IWM['Date'] = pd.to_datetime(SPY['Date'])
unemployment['Date'] = pd.to_datetime(unemployment['Date'])
In [29]:
iwm_data=IWM
qqq_data=QQQ
spy_data=SPY
unemployment_data=unemployment
In [30]:
# Merge the unemployment rate data with each ETF dataset on the 'Date' column
# First, ensure the 'Date' column in unemployment data is in datetime format for proper merging
unemployment_data = data
unemployment_data['Date'] = pd.to_datetime(unemployment_data['Date'])

# Merge operations
merged_iwm = pd.merge(iwm_data, unemployment_data, on='Date', how='inner')
merged_qqq = pd.merge(qqq_data, unemployment_data, on='Date', how='inner')
merged_spy = pd.merge(spy_data, unemployment_data, on='Date', how='inner')

# Display the merged data head for one ETF as example
merged_qqq.head()
Out[30]:
Date Open High Low Close Adj Close Volume SPY_Open SPY_High SPY_Low ... IWM_Open IWM_High IWM_Low IWM_Close IWM_Adj Close IWM_Volume unemployment_Actual unemployment_Forecast unemployment_Previous Announcement_Day
0 2018-01-02 156.559998 158.529999 156.169998 158.490005 151.871933 32573300 267.839996 268.809998 267.399994 ... 153.199997 153.970001 152.460007 153.899994 141.990631 20489600.0 NaN NaN NaN False
1 2018-01-03 158.639999 160.169998 158.610001 160.029999 153.347641 29383600 268.959991 270.640015 268.959991 ... 153.869995 154.460007 153.520004 154.059998 142.138260 21836600.0 NaN NaN NaN False
2 2018-01-04 160.580002 160.789993 160.080002 160.309998 153.615906 24776100 271.200012 272.160004 270.540009 ... 154.970001 155.149994 154.020004 154.470001 142.516525 14207100.0 NaN NaN NaN False
3 2018-01-05 161.070007 162.029999 160.770004 161.919998 155.158768 26992300 272.510010 273.559998 271.950012 ... 154.880005 154.979996 153.940002 154.789993 142.811752 19883900.0 4.10% 4.10% 4.10% True
4 2018-01-08 161.919998 162.630005 161.860001 162.550003 155.762390 23159100 273.309998 274.100006 272.980011 ... 154.729996 155.270004 153.500000 155.029999 143.033173 18457300.0 4.10% 4.10% 4.10% False

5 rows × 29 columns

In [31]:
# Function to calculate daily returns
def calculate_returns(df):
    df['Daily Returns'] = df['Adj Close'].pct_change()
    return df

# Apply the function to calculate daily returns for each ETF dataset
iwm_data = calculate_returns(iwm_data)
qqq_data = calculate_returns(qqq_data)
spy_data = calculate_returns(spy_data)

# Function to extract event and estimation windows
def extract_windows(event_df, full_df, days_event=5, days_estimation=30):
    # Dictionary to hold event and estimation windows data
    windows_data = {'Event Window': [], 'Estimation Window': []}
    
    for index, row in event_df.iterrows():
        event_date = row['Date']
        
        # Get the indices for the event date
        event_idx = full_df[full_df['Date'] == event_date].index[0]
        
        # Extract the event window data
        start_event = event_idx - 2  # Start from 2 days before the event
        end_event = event_idx + 2   # End at 2 days after the event
        event_window = full_df.iloc[start_event:end_event + 1]
        
        # Extract the estimation window data
        start_estimation = event_idx - days_estimation - 2  # Start 30 days before the event window
        end_estimation = event_idx - 3  # End just before the event window starts
        estimation_window = full_df.iloc[start_estimation:end_estimation + 1]
        
        windows_data['Event Window'].append(event_window)
        windows_data['Estimation Window'].append(estimation_window)
    
    return windows_data

# Extract windows for each ETF
iwm_windows = extract_windows(merged_iwm, iwm_data)
qqq_windows = extract_windows(merged_qqq, qqq_data)
spy_windows = extract_windows(merged_spy, spy_data)

# Checking the first extracted windows as an example
iwm_windows['Event Window'][0].head(), iwm_windows['Estimation Window'][0].head()
Out[31]:
(Empty DataFrame
 Columns: [Date, Open, High, Low, Close, Adj Close, Volume, Daily Returns]
 Index: [],
            Date        Open        High         Low       Close   Adj Close  \
 1553 2024-03-06  206.029999  206.080002  204.080002  205.250000  204.730148   
 1554 2024-03-07  206.699997  208.100006  206.399994  206.960007  206.435822   
 1555 2024-03-08  208.740005  210.410004  205.800003  206.830002  206.306152   
 1556 2024-03-11  205.960007  206.839996  204.750000  205.190002  204.670303   
 1557 2024-03-12  205.149994  205.919998  203.389999  204.910004  204.391006   
 
         Volume  Daily Returns  
 1553  34255200       0.007461  
 1554  28020200       0.008331  
 1555  41430500      -0.000628  
 1556  24435800      -0.007929  
 1557  34958900      -0.001365  )
In [32]:
# Adjusting the function to ensure we correctly handle edge cases with estimation window extraction

def extract_windows_adjusted(event_df, full_df, days_event=5, days_estimation=30):
    # Dictionary to hold event and estimation windows data
    windows_data = {'Event Window': [], 'Estimation Window': []}
    
    for index, row in event_df.iterrows():
        event_date = row['Date']
        
        # Get the indices for the event date
        event_idx = full_df[full_df['Date'] == event_date].index[0]
        
        # Check for boundaries
        max_idx = len(full_df) - 1
        min_idx = 0
        
        # Define indices for event window with boundary checks
        start_event = max(min_idx, event_idx - 2)  # Start from 2 days before the event
        end_event = min(max_idx, event_idx + 2)  # End at 2 days after the event
        event_window = full_df.iloc[start_event:end_event + 1]
        
        # Define indices for estimation window with boundary checks
        start_estimation = max(min_idx, event_idx - days_estimation - 2)  # Start 30 days before the event window
        end_estimation = max(min_idx, event_idx - 3)  # End just before the event window starts
        estimation_window = full_df.iloc[start_estimation:end_estimation + 1]
        
        windows_data['Event Window'].append(event_window)
        windows_data['Estimation Window'].append(estimation_window)
    
    return windows_data

# Re-extract windows with adjusted logic
iwm_windows_adjusted = extract_windows_adjusted(merged_iwm, iwm_data)
qqq_windows_adjusted = extract_windows_adjusted(merged_qqq, qqq_data)
spy_windows_adjusted = extract_windows_adjusted(merged_spy, spy_data)

# Checking the first extracted windows again for IWM as an example
iwm_windows_adjusted['Event Window'][0].head(), iwm_windows_adjusted['Estimation Window'][0].head()
Out[32]:
(        Date        Open        High         Low       Close   Adj Close  \
 0 2018-01-02  153.199997  153.970001  152.460007  153.899994  141.990631   
 1 2018-01-03  153.869995  154.460007  153.520004  154.059998  142.138260   
 2 2018-01-04  154.970001  155.149994  154.020004  154.470001  142.516525   
 
      Volume  Daily Returns  
 0  20489600            NaN  
 1  21836600       0.001040  
 2  14207100       0.002661  ,
         Date        Open        High         Low       Close   Adj Close  \
 0 2018-01-02  153.199997  153.970001  152.460007  153.899994  141.990631   
 
      Volume  Daily Returns  
 0  20489600            NaN  )
In [33]:
qqq_windows_adjusted
Out[33]:
{'Event Window': [        Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  ,
          Date        Open        High         Low       Close   Adj Close  \
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  
       Volume  Daily Returns  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  ,
          Date        Open        High         Low       Close   Adj Close  \
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  
       Volume  Daily Returns  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  ,
          Date        Open        High         Low       Close   Adj Close  \
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  
       Volume  Daily Returns  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  ,
          Date        Open        High         Low       Close   Adj Close  \
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8 2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  
       Volume  Daily Returns  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  
  8  37762700       0.007349  ,
          Date        Open        High         Low       Close   Adj Close  \
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8 2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9 2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  
       Volume  Daily Returns  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  
  8  37762700       0.007349  
  9  41231800      -0.002857  ,
           Date        Open        High         Low       Close   Adj Close  \
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  
        Volume  Daily Returns  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  ,
           Date        Open        High         Low       Close   Adj Close  \
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  
        Volume  Daily Returns  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  ,
           Date        Open        High         Low       Close   Adj Close  \
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  
        Volume  Daily Returns  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  ,
           Date        Open        High         Low       Close   Adj Close  \
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  
        Volume  Daily Returns  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  ,
           Date        Open        High         Low       Close   Adj Close  \
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  
        Volume  Daily Returns  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  ,
           Date        Open        High         Low       Close   Adj Close  \
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  
        Volume  Daily Returns  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  ,
           Date        Open        High         Low       Close   Adj Close  \
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  
        Volume  Daily Returns  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  ,
           Date        Open        High         Low       Close   Adj Close  \
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  
        Volume  Daily Returns  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  ,
           Date        Open        High         Low       Close   Adj Close  \
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  
        Volume  Daily Returns  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  ,
           Date        Open        High         Low       Close   Adj Close  \
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  
        Volume  Daily Returns  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  ,
           Date        Open        High         Low       Close   Adj Close  \
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  
        Volume  Daily Returns  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  ,
           Date        Open        High         Low       Close   Adj Close  \
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  
        Volume  Daily Returns  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  
  21  38037900      -0.008501  ,
           Date        Open        High         Low       Close   Adj Close  \
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  
        Volume  Daily Returns  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  
  21  38037900      -0.008501  
  22  68478100      -0.019945  ,
           Date        Open        High         Low       Close   Adj Close  \
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  
         Volume  Daily Returns  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  ,
           Date        Open        High         Low       Close   Adj Close  \
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  
         Volume  Daily Returns  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  ,
           Date        Open        High         Low       Close   Adj Close  \
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  
         Volume  Daily Returns  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  ,
           Date        Open        High         Low       Close   Adj Close  \
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  
         Volume  Daily Returns  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  ,
           Date        Open        High         Low       Close   Adj Close  \
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  
         Volume  Daily Returns  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  ,
           Date        Open        High         Low       Close   Adj Close  \
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  
         Volume  Daily Returns  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  ,
           Date        Open        High         Low       Close   Adj Close  \
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  
         Volume  Daily Returns  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  ,
           Date        Open        High         Low       Close   Adj Close  \
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  
         Volume  Daily Returns  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  ,
           Date        Open        High         Low       Close   Adj Close  \
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  
         Volume  Daily Returns  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  ,
           Date        Open        High         Low       Close   Adj Close  \
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  
        Volume  Daily Returns  
  28  63050600       0.017745  
  29  31785600       0.005161  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  ,
           Date        Open        High         Low       Close   Adj Close  \
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  
        Volume  Daily Returns  
  29  31785600       0.005161  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  ,
           Date        Open        High         Low       Close   Adj Close  \
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  
        Volume  Daily Returns  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  ,
           Date        Open        High         Low       Close   Adj Close  \
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  
        Volume  Daily Returns  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  ,
           Date        Open        High         Low       Close   Adj Close  \
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  
        Volume  Daily Returns  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  ,
           Date        Open        High         Low       Close   Adj Close  \
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  
        Volume  Daily Returns  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  ,
           Date        Open        High         Low       Close   Adj Close  \
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  
        Volume  Daily Returns  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  ,
           Date        Open        High         Low       Close   Adj Close  \
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  
        Volume  Daily Returns  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  ,
           Date        Open        High         Low       Close   Adj Close  \
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  
        Volume  Daily Returns  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  ,
           Date        Open        High         Low       Close   Adj Close  \
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  
        Volume  Daily Returns  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  ,
           Date        Open        High         Low       Close   Adj Close  \
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  
        Volume  Daily Returns  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  ,
           Date        Open        High         Low       Close   Adj Close  \
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  
        Volume  Daily Returns  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  ,
           Date        Open        High         Low       Close   Adj Close  \
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  
        Volume  Daily Returns  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  ,
           Date        Open        High         Low       Close   Adj Close  \
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  
        Volume  Daily Returns  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  ,
           Date        Open        High         Low       Close   Adj Close  \
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  
        Volume  Daily Returns  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  ,
           Date        Open        High         Low       Close   Adj Close  \
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  
        Volume  Daily Returns  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  ,
           Date        Open        High         Low       Close   Adj Close  \
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  
        Volume  Daily Returns  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  ,
           Date        Open        High         Low       Close   Adj Close  \
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  
        Volume  Daily Returns  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  ,
           Date        Open        High         Low       Close   Adj Close  \
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  
        Volume  Daily Returns  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  ,
           Date        Open        High         Low       Close   Adj Close  \
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  
        Volume  Daily Returns  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  ,
           Date        Open        High         Low       Close   Adj Close  \
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  
        Volume  Daily Returns  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  ,
           Date        Open        High         Low       Close   Adj Close  \
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  
        Volume  Daily Returns  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  ,
           Date        Open        High         Low       Close   Adj Close  \
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  
        Volume  Daily Returns  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  ,
           Date        Open        High         Low       Close   Adj Close  \
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  
        Volume  Daily Returns  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  ,
           Date        Open        High         Low       Close   Adj Close  \
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  
        Volume  Daily Returns  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  ,
           Date        Open        High         Low       Close   Adj Close  \
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  
        Volume  Daily Returns  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  ,
           Date        Open        High         Low       Close   Adj Close  \
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  
        Volume  Daily Returns  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  ,
           Date        Open        High         Low       Close   Adj Close  \
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  
        Volume  Daily Returns  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  ,
           Date        Open        High         Low       Close   Adj Close  \
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  
        Volume  Daily Returns  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  ,
           Date        Open        High         Low       Close   Adj Close  \
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  
        Volume  Daily Returns  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  ,
           Date        Open        High         Low       Close   Adj Close  \
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  
        Volume  Daily Returns  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  ,
           Date        Open        High         Low       Close   Adj Close  \
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  
        Volume  Daily Returns  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  ,
           Date        Open        High         Low       Close   Adj Close  \
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  
        Volume  Daily Returns  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  ,
           Date        Open        High         Low       Close   Adj Close  \
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  
        Volume  Daily Returns  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  ,
           Date        Open        High         Low       Close   Adj Close  \
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  
        Volume  Daily Returns  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  ,
           Date        Open        High         Low       Close   Adj Close  \
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  
        Volume  Daily Returns  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  ,
           Date        Open        High         Low       Close   Adj Close  \
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  
        Volume  Daily Returns  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  ,
           Date        Open        High         Low       Close   Adj Close  \
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  
        Volume  Daily Returns  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  ,
           Date        Open        High         Low       Close   Adj Close  \
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  
        Volume  Daily Returns  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  ,
           Date        Open        High         Low       Close   Adj Close  \
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  
        Volume  Daily Returns  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  ,
           Date        Open        High         Low       Close   Adj Close  \
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  
        Volume  Daily Returns  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  ,
           Date        Open        High         Low       Close   Adj Close  \
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  
        Volume  Daily Returns  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  ,
           Date        Open        High         Low       Close   Adj Close  \
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  
        Volume  Daily Returns  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  ,
           Date        Open        High         Low       Close   Adj Close  \
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  
        Volume  Daily Returns  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  ,
           Date        Open        High         Low       Close   Adj Close  \
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  
        Volume  Daily Returns  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  ,
           Date        Open        High         Low       Close   Adj Close  \
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  
        Volume  Daily Returns  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  ,
           Date        Open        High         Low       Close   Adj Close  \
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  
        Volume  Daily Returns  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  ,
           Date        Open        High         Low       Close   Adj Close  \
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  
        Volume  Daily Returns  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  ,
           Date        Open        High         Low       Close   Adj Close  \
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  
        Volume  Daily Returns  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  ,
           Date        Open        High         Low       Close   Adj Close  \
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  
        Volume  Daily Returns  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  ,
           Date        Open        High         Low       Close   Adj Close  \
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  
        Volume  Daily Returns  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  ,
           Date        Open        High         Low       Close   Adj Close  \
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  
        Volume  Daily Returns  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  ,
           Date        Open        High         Low       Close   Adj Close  \
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  
        Volume  Daily Returns  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  ,
           Date        Open        High         Low       Close   Adj Close  \
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  
        Volume  Daily Returns  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  ,
           Date        Open        High         Low       Close   Adj Close  \
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  
        Volume  Daily Returns  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  ,
           Date        Open        High         Low       Close   Adj Close  \
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  
        Volume  Daily Returns  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  ,
           Date        Open        High         Low       Close   Adj Close  \
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  
        Volume  Daily Returns  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  ,
           Date        Open        High         Low       Close   Adj Close  \
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  
        Volume  Daily Returns  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  ,
           Date        Open        High         Low       Close   Adj Close  \
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  
        Volume  Daily Returns  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  ,
           Date        Open        High         Low       Close   Adj Close  \
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  
        Volume  Daily Returns  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  ,
           Date        Open        High         Low       Close   Adj Close  \
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  
        Volume  Daily Returns  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  ,
           Date        Open        High         Low       Close   Adj Close  \
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  
        Volume  Daily Returns  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  ,
           Date        Open        High         Low       Close   Adj Close  \
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  
        Volume  Daily Returns  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  ,
           Date        Open        High         Low       Close   Adj Close  \
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  
        Volume  Daily Returns  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  ,
           Date        Open        High         Low       Close   Adj Close  \
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  
        Volume  Daily Returns  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  ,
           Date        Open        High         Low       Close   Adj Close  \
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  
        Volume  Daily Returns  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  ,
           Date        Open        High         Low       Close   Adj Close  \
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98 2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  
        Volume  Daily Returns  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  
  98  26557800       0.008443  ,
           Date        Open        High         Low       Close   Adj Close  \
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98 2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99 2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  
        Volume  Daily Returns  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  
  98  26557800       0.008443  
  99  27696500      -0.000295  ,
            Date        Open        High         Low       Close   Adj Close  \
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  
         Volume  Daily Returns  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  ,
            Date        Open        High         Low       Close   Adj Close  \
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  
         Volume  Daily Returns  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  ,
            Date        Open        High         Low       Close   Adj Close  \
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  
         Volume  Daily Returns  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  ,
            Date        Open        High         Low       Close   Adj Close  \
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  
         Volume  Daily Returns  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  ,
            Date        Open        High         Low       Close   Adj Close  \
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  
         Volume  Daily Returns  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  ,
            Date        Open        High         Low       Close   Adj Close  \
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  
         Volume  Daily Returns  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  ,
            Date        Open        High         Low       Close   Adj Close  \
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  
         Volume  Daily Returns  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  ,
            Date        Open        High         Low       Close   Adj Close  \
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  
         Volume  Daily Returns  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  ,
            Date        Open        High         Low       Close   Adj Close  \
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  
         Volume  Daily Returns  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  ,
            Date        Open        High         Low       Close   Adj Close  \
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  
         Volume  Daily Returns  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  ,
            Date        Open        High         Low       Close   Adj Close  \
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  
         Volume  Daily Returns  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  ,
            Date        Open        High         Low       Close   Adj Close  \
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  
         Volume  Daily Returns  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  ,
            Date        Open        High         Low       Close   Adj Close  \
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  
         Volume  Daily Returns  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  ,
            Date        Open        High         Low       Close   Adj Close  \
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  
         Volume  Daily Returns  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  ,
            Date        Open        High         Low       Close   Adj Close  \
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  
         Volume  Daily Returns  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  ,
            Date        Open        High         Low       Close   Adj Close  \
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  
         Volume  Daily Returns  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  ,
            Date        Open        High         Low       Close   Adj Close  \
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  
         Volume  Daily Returns  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  ,
            Date        Open        High         Low       Close   Adj Close  \
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  
         Volume  Daily Returns  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  ,
            Date        Open        High         Low       Close   Adj Close  \
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  
         Volume  Daily Returns  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  ,
            Date        Open        High         Low       Close   Adj Close  \
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  
         Volume  Daily Returns  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  ,
            Date        Open        High         Low       Close   Adj Close  \
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  
         Volume  Daily Returns  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  ,
            Date        Open        High         Low       Close   Adj Close  \
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  
         Volume  Daily Returns  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  ,
            Date        Open        High         Low       Close   Adj Close  \
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  
         Volume  Daily Returns  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  ,
            Date        Open        High         Low       Close   Adj Close  \
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  
         Volume  Daily Returns  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  ,
            Date        Open        High         Low       Close   Adj Close  \
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  
         Volume  Daily Returns  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  ,
            Date        Open        High         Low       Close   Adj Close  \
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  
         Volume  Daily Returns  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  ,
            Date        Open        High         Low       Close   Adj Close  \
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  
         Volume  Daily Returns  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  ,
            Date        Open        High         Low       Close   Adj Close  \
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  
         Volume  Daily Returns  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  ,
            Date        Open        High         Low       Close   Adj Close  \
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  
         Volume  Daily Returns  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  ,
            Date        Open        High         Low       Close   Adj Close  \
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  
         Volume  Daily Returns  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  ,
            Date        Open        High         Low       Close   Adj Close  \
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  
         Volume  Daily Returns  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  ,
            Date        Open        High         Low       Close   Adj Close  \
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  
         Volume  Daily Returns  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  ,
            Date        Open        High         Low       Close   Adj Close  \
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  
         Volume  Daily Returns  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  ,
            Date        Open        High         Low       Close   Adj Close  \
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  
         Volume  Daily Returns  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  ,
            Date        Open        High         Low       Close   Adj Close  \
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  
         Volume  Daily Returns  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  ,
            Date        Open        High         Low       Close   Adj Close  \
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  
         Volume  Daily Returns  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  ,
            Date        Open        High         Low       Close   Adj Close  \
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  
         Volume  Daily Returns  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  ,
            Date        Open        High         Low       Close   Adj Close  \
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  
         Volume  Daily Returns  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  ,
            Date        Open        High         Low       Close   Adj Close  \
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  
         Volume  Daily Returns  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  ,
            Date        Open        High         Low       Close   Adj Close  \
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  
         Volume  Daily Returns  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  ,
            Date        Open        High         Low       Close   Adj Close  \
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  
         Volume  Daily Returns  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  ,
            Date        Open        High         Low       Close   Adj Close  \
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  
         Volume  Daily Returns  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  ,
            Date        Open        High         Low       Close   Adj Close  \
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  
         Volume  Daily Returns  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  ,
            Date        Open        High         Low       Close   Adj Close  \
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  
         Volume  Daily Returns  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  ,
            Date        Open        High         Low       Close   Adj Close  \
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  
         Volume  Daily Returns  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  ,
            Date        Open        High         Low       Close   Adj Close  \
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  
         Volume  Daily Returns  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  ,
            Date        Open        High         Low       Close   Adj Close  \
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  
         Volume  Daily Returns  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  ,
            Date        Open        High         Low       Close   Adj Close  \
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  
         Volume  Daily Returns  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  ,
            Date        Open        High         Low       Close   Adj Close  \
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  
         Volume  Daily Returns  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  ,
            Date        Open        High         Low       Close   Adj Close  \
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  
         Volume  Daily Returns  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  ,
            Date        Open        High         Low       Close   Adj Close  \
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  
         Volume  Daily Returns  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  ,
            Date        Open        High         Low       Close   Adj Close  \
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  
         Volume  Daily Returns  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  ,
            Date        Open        High         Low       Close   Adj Close  \
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  
         Volume  Daily Returns  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  ,
            Date        Open        High         Low       Close   Adj Close  \
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  
         Volume  Daily Returns  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  ,
            Date        Open        High         Low       Close   Adj Close  \
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  
         Volume  Daily Returns  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  ,
            Date        Open        High         Low       Close   Adj Close  \
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  
         Volume  Daily Returns  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  ,
            Date        Open        High         Low       Close   Adj Close  \
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  
         Volume  Daily Returns  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  ,
            Date        Open        High         Low       Close   Adj Close  \
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  
         Volume  Daily Returns  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  ,
            Date        Open        High         Low       Close   Adj Close  \
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  
         Volume  Daily Returns  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  ,
            Date        Open        High         Low       Close   Adj Close  \
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  
         Volume  Daily Returns  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  ,
            Date        Open        High         Low       Close   Adj Close  \
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  
         Volume  Daily Returns  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  ,
            Date        Open        High         Low       Close   Adj Close  \
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  
         Volume  Daily Returns  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  ,
            Date        Open        High         Low       Close   Adj Close  \
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  
         Volume  Daily Returns  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  ,
            Date        Open        High         Low       Close   Adj Close  \
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  
         Volume  Daily Returns  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  ,
            Date        Open        High         Low       Close   Adj Close  \
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  
         Volume  Daily Returns  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  ,
            Date        Open        High         Low       Close   Adj Close  \
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  
         Volume  Daily Returns  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  ,
            Date        Open        High         Low       Close   Adj Close  \
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  
         Volume  Daily Returns  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  ,
            Date        Open        High         Low       Close   Adj Close  \
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  
         Volume  Daily Returns  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  ,
            Date        Open        High         Low       Close   Adj Close  \
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  
         Volume  Daily Returns  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  ,
            Date        Open        High         Low       Close   Adj Close  \
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  
         Volume  Daily Returns  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  ,
            Date        Open        High         Low       Close   Adj Close  \
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  
         Volume  Daily Returns  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  ,
            Date        Open        High         Low       Close   Adj Close  \
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  
         Volume  Daily Returns  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  ,
            Date        Open        High         Low       Close   Adj Close  \
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  
         Volume  Daily Returns  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  ,
            Date        Open        High         Low       Close   Adj Close  \
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  
         Volume  Daily Returns  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  ,
            Date        Open        High         Low       Close   Adj Close  \
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  
         Volume  Daily Returns  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  ,
            Date        Open        High         Low       Close   Adj Close  \
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  
         Volume  Daily Returns  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  ,
            Date        Open        High         Low       Close   Adj Close  \
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  
         Volume  Daily Returns  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  ,
            Date        Open        High         Low       Close   Adj Close  \
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  
         Volume  Daily Returns  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  ,
            Date        Open        High         Low       Close   Adj Close  \
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  
         Volume  Daily Returns  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  ,
            Date        Open        High         Low       Close   Adj Close  \
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  
         Volume  Daily Returns  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  ,
            Date        Open        High         Low       Close   Adj Close  \
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  
         Volume  Daily Returns  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  ,
            Date        Open        High         Low       Close   Adj Close  \
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  
         Volume  Daily Returns  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  ,
            Date        Open        High         Low       Close   Adj Close  \
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  
         Volume  Daily Returns  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  ,
            Date        Open        High         Low       Close   Adj Close  \
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  
         Volume  Daily Returns  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  ,
            Date        Open        High         Low       Close   Adj Close  \
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  
         Volume  Daily Returns  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  ,
            Date        Open        High         Low       Close   Adj Close  \
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  
         Volume  Daily Returns  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  ,
            Date        Open        High         Low       Close   Adj Close  \
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  
         Volume  Daily Returns  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  ,
            Date        Open        High         Low       Close   Adj Close  \
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  
         Volume  Daily Returns  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  ,
            Date        Open        High         Low       Close   Adj Close  \
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  
         Volume  Daily Returns  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  ,
            Date        Open        High         Low       Close   Adj Close  \
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  
         Volume  Daily Returns  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  ,
            Date        Open        High         Low       Close   Adj Close  \
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  
         Volume  Daily Returns  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  ,
            Date        Open        High         Low       Close   Adj Close  \
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  
         Volume  Daily Returns  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  ,
            Date        Open        High         Low       Close   Adj Close  \
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  
         Volume  Daily Returns  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  ,
            Date        Open        High         Low       Close   Adj Close  \
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  
         Volume  Daily Returns  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  
  193  66864500      -0.006106  ,
            Date        Open        High         Low       Close   Adj Close  \
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  
         Volume  Daily Returns  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  
  193  66864500      -0.006106  
  194  49097900       0.003239  ,
            Date        Open        High         Low       Close   Adj Close  \
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  
          Volume  Daily Returns  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  ,
            Date        Open        High         Low       Close   Adj Close  \
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  
          Volume  Daily Returns  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  ,
            Date        Open        High         Low       Close   Adj Close  \
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  
          Volume  Daily Returns  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  ,
            Date        Open        High         Low       Close   Adj Close  \
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  
          Volume  Daily Returns  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  ,
            Date        Open        High         Low       Close   Adj Close  \
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  
          Volume  Daily Returns  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  ,
            Date        Open        High         Low       Close   Adj Close  \
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  
          Volume  Daily Returns  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  ,
            Date        Open        High         Low       Close   Adj Close  \
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  
          Volume  Daily Returns  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  ,
            Date        Open        High         Low       Close   Adj Close  \
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  
         Volume  Daily Returns  
  198  64885300      -0.012104  
  199  71979700       0.029092  
  200  66987600       0.000395  
  201  82486200      -0.023182  
  202  82923700      -0.000924  ,
            Date        Open        High         Low       Close   Adj Close  \
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  
         Volume  Daily Returns  
  199  71979700       0.029092  
  200  66987600       0.000395  
  201  82486200      -0.023182  
  202  82923700      -0.000924  
  203  52909300       0.005144  ,
            Date        Open        High         Low       Close   Adj Close  \
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  
         Volume  Daily Returns  
  200  66987600       0.000395  
  201  82486200      -0.023182  
  202  82923700      -0.000924  
  203  52909300       0.005144  
  204  77567000      -0.003680  ,
            Date        Open        High         Low       Close   Adj Close  \
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  
          Volume  Daily Returns  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  ,
            Date        Open        High         Low       Close   Adj Close  \
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  
          Volume  Daily Returns  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  ,
            Date        Open        High         Low       Close   Adj Close  \
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  
          Volume  Daily Returns  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  ,
            Date        Open        High         Low       Close   Adj Close  \
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  
          Volume  Daily Returns  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  ,
            Date        Open        High         Low       Close   Adj Close  \
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  
          Volume  Daily Returns  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  ,
            Date        Open        High         Low       Close   Adj Close  \
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  
          Volume  Daily Returns  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  ,
            Date        Open        High         Low       Close   Adj Close  \
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  
          Volume  Daily Returns  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  ,
            Date        Open        High         Low       Close   Adj Close  \
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  
          Volume  Daily Returns  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  ,
            Date        Open        High         Low       Close   Adj Close  \
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  
         Volume  Daily Returns  
  209  92584000       0.016480  
  210  73828600       0.023505  
  211  52706800       0.013190  
  212  75966800      -0.015576  
  213  39573500      -0.002479  ,
            Date        Open        High         Low       Close   Adj Close  \
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  
         Volume  Daily Returns  
  210  73828600       0.023505  
  211  52706800       0.013190  
  212  75966800      -0.015576  
  213  39573500      -0.002479  
  214  34410400       0.007576  ,
            Date        Open        High         Low       Close   Adj Close  \
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  
         Volume  Daily Returns  
  211  52706800       0.013190  
  212  75966800      -0.015576  
  213  39573500      -0.002479  
  214  34410400       0.007576  
  215  51169600       0.031368  ,
            Date        Open        High         Low       Close   Adj Close  \
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  
         Volume  Daily Returns  
  212  75966800      -0.015576  
  213  39573500      -0.002479  
  214  34410400       0.007576  
  215  51169600       0.031368  
  216  40296500      -0.006379  ,
            Date        Open        High         Low       Close   Adj Close  \
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  
         Volume  Daily Returns  
  213  39573500      -0.002479  
  214  34410400       0.007576  
  215  51169600       0.031368  
  216  40296500      -0.006379  
  217  50602700      -0.016852  ,
            Date        Open        High         Low       Close   Adj Close  \
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  
         Volume  Daily Returns  
  214  34410400       0.007576  
  215  51169600       0.031368  
  216  40296500      -0.006379  
  217  50602700      -0.016852  
  218  62578400      -0.030259  ,
            Date        Open        High         Low       Close   Adj Close  \
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  
         Volume  Daily Returns  
  215  51169600       0.031368  
  216  40296500      -0.006379  
  217  50602700      -0.016852  
  218  62578400      -0.030259  
  219  64128100       0.000842  ,
            Date        Open        High         Low       Close   Adj Close  \
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  
         Volume  Daily Returns  
  216  40296500      -0.006379  
  217  50602700      -0.016852  
  218  62578400      -0.030259  
  219  64128100       0.000842  
  220  75270700      -0.007629  ,
            Date        Open        High         Low       Close   Adj Close  \
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  
         Volume  Daily Returns  
  217  50602700      -0.016852  
  218  62578400      -0.030259  
  219  64128100       0.000842  
  220  75270700      -0.007629  
  221  73254300       0.017494  ,
            Date        Open        High         Low       Close   Adj Close  \
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  
         Volume  Daily Returns  
  218  62578400      -0.030259  
  219  64128100       0.000842  
  220  75270700      -0.007629  
  221  73254300       0.017494  
  222  65390700      -0.003510  ,
            Date        Open        High         Low       Close   Adj Close  \
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  
         Volume  Daily Returns  
  219  64128100       0.000842  
  220  75270700      -0.007629  
  221  73254300       0.017494  
  222  65390700      -0.003510  
  223  67280500      -0.032477  ,
            Date        Open        High         Low       Close   Adj Close  \
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  
          Volume  Daily Returns  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  ,
            Date        Open        High         Low       Close   Adj Close  \
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  
          Volume  Daily Returns  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  ,
            Date        Open        High         Low       Close   Adj Close  \
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  
          Volume  Daily Returns  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  ,
            Date        Open        High         Low       Close   Adj Close  \
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  
          Volume  Daily Returns  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  ,
            Date        Open        High         Low       Close   Adj Close  \
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  
          Volume  Daily Returns  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  ,
            Date        Open        High         Low       Close   Adj Close  \
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  
         Volume  Daily Returns  
  225  42965800       0.007603  
  226  23503700      -0.007233  
  227  42012600       0.023114  
  228  36608100       0.003376  
  229  70141000       0.032183  ,
            Date        Open        High         Low       Close   Adj Close  \
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  
         Volume  Daily Returns  
  226  23503700      -0.007233  
  227  42012600       0.023114  
  228  36608100       0.003376  
  229  70141000       0.032183  
  230  44885700      -0.003260  ,
            Date        Open        High         Low       Close   Adj Close  \
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  
         Volume  Daily Returns  
  227  42012600       0.023114  
  228  36608100       0.003376  
  229  70141000       0.032183  
  230  44885700      -0.003260  
  231  36722800       0.007255  ,
            Date        Open        High         Low       Close   Adj Close  \
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  
         Volume  Daily Returns  
  228  36608100       0.003376  
  229  70141000       0.032183  
  230  44885700      -0.003260  
  231  36722800       0.007255  
  232  50771700       0.017476  ,
            Date        Open        High         Low       Close   Adj Close  \
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  
         Volume  Daily Returns  
  229  70141000       0.032183  
  230  44885700      -0.003260  
  231  36722800       0.007255  
  232  50771700       0.017476  
  233  70594700      -0.038357  ,
            Date        Open        High         Low       Close   Adj Close  \
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  
         Volume  Daily Returns  
  230  44885700      -0.003260  
  231  36722800       0.007255  
  232  50771700       0.017476  
  233  70594700      -0.038357  
  234  71715500       0.007060  ,
            Date        Open        High         Low       Close   Adj Close  \
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  
         Volume  Daily Returns  
  231  36722800       0.007255  
  232  50771700       0.017476  
  233  70594700      -0.038357  
  234  71715500       0.007060  
  235  80432200      -0.033016  ,
            Date        Open        High         Low       Close   Adj Close  \
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  
         Volume  Daily Returns  
  232  50771700       0.017476  
  233  70594700      -0.038357  
  234  71715500       0.007060  
  235  80432200      -0.033016  
  236  73960800       0.010472  ,
            Date        Open        High         Low       Close   Adj Close  \
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  
         Volume  Daily Returns  
  233  70594700      -0.038357  
  234  71715500       0.007060  
  235  80432200      -0.033016  
  236  73960800       0.010472  
  237  59058300       0.003311  ,
            Date        Open        High         Low       Close   Adj Close  \
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  
         Volume  Daily Returns  
  234  71715500       0.007060  
  235  80432200      -0.033016  
  236  73960800       0.010472  
  237  59058300       0.003311  
  238  53780000       0.008801  ,
            Date        Open        High         Low       Close   Adj Close  \
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  
         Volume  Daily Returns  
  235  80432200      -0.033016  
  236  73960800       0.010472  
  237  59058300       0.003311  
  238  53780000       0.008801  
  239  46378500       0.000303  ,
            Date        Open        High         Low       Close   Adj Close  \
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  
         Volume  Daily Returns  
  236  73960800       0.010472  
  237  59058300       0.003311  
  238  53780000       0.008801  
  239  46378500       0.000303  
  240  56547400      -0.024349  ,
            Date        Open        High         Low       Close   Adj Close  \
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  
         Volume  Daily Returns  
  237  59058300       0.003311  
  238  53780000       0.008801  
  239  46378500       0.000303  
  240  56547400      -0.024349  
  241  74834100      -0.022660  ,
            Date        Open        High         Low       Close   Adj Close  \
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  
         Volume  Daily Returns  
  238  53780000       0.008801  
  239  46378500       0.000303  
  240  56547400      -0.024349  
  241  74834100      -0.022660  
  242  63642100       0.006289  ,
            Date        Open        High         Low       Close   Adj Close  \
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  
         Volume  Daily Returns  
  239  46378500       0.000303  
  240  56547400      -0.024349  
  241  74834100      -0.022660  
  242  63642100       0.006289  
  243  81856500      -0.024555  ,
            Date        Open        High         Low       Close   Adj Close  \
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  
         Volume  Daily Returns  
  240  56547400      -0.024349  
  241  74834100      -0.022660  
  242  63642100       0.006289  
  243  81856500      -0.024555  
  244  99002100      -0.014496  ,
            Date        Open        High         Low       Close   Adj Close  \
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  
          Volume  Daily Returns  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  ,
            Date        Open        High         Low       Close   Adj Close  \
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  
          Volume  Daily Returns  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  ,
            Date        Open        High         Low       Close   Adj Close  \
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  
          Volume  Daily Returns  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  ,
            Date        Open        High         Low       Close   Adj Close  \
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  
          Volume  Daily Returns  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  ,
            Date        Open        High         Low       Close   Adj Close  \
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  
          Volume  Daily Returns  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  ,
            Date        Open        High         Low       Close   Adj Close  \
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  
         Volume  Daily Returns  
  246  56163300      -0.024798  
  247  98982100       0.062439  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  ,
            Date        Open        High         Low       Close   Adj Close  \
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  
         Volume  Daily Returns  
  247  98982100       0.062439  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  ,
            Date        Open        High         Low       Close   Adj Close  \
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  
         Volume  Daily Returns  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  ,
            Date        Open        High         Low       Close   Adj Close  \
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  
         Volume  Daily Returns  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  ,
            Date        Open        High         Low       Close   Adj Close  \
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  
         Volume  Daily Returns  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  ,
            Date        Open        High         Low       Close   Adj Close  \
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  
         Volume  Daily Returns  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  ,
            Date        Open        High         Low       Close   Adj Close  \
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  
         Volume  Daily Returns  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  ,
            Date        Open        High         Low       Close   Adj Close  \
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  
         Volume  Daily Returns  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  ,
            Date        Open        High         Low       Close   Adj Close  \
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  
         Volume  Daily Returns  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  ,
            Date        Open        High         Low       Close   Adj Close  \
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  
         Volume  Daily Returns  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  ,
            Date        Open        High         Low       Close   Adj Close  \
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  
         Volume  Daily Returns  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  ,
            Date        Open        High         Low       Close   Adj Close  \
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  
         Volume  Daily Returns  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  ,
            Date        Open        High         Low       Close   Adj Close  \
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  
         Volume  Daily Returns  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  ,
            Date        Open        High         Low       Close   Adj Close  \
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  
         Volume  Daily Returns  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  ,
            Date        Open        High         Low       Close   Adj Close  \
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  
         Volume  Daily Returns  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  ,
            Date        Open        High         Low       Close   Adj Close  \
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  
         Volume  Daily Returns  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  ,
            Date        Open        High         Low       Close   Adj Close  \
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  
         Volume  Daily Returns  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  ,
            Date        Open        High         Low       Close   Adj Close  \
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  
         Volume  Daily Returns  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  ,
            Date        Open        High         Low       Close   Adj Close  \
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  
         Volume  Daily Returns  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  ,
            Date        Open        High         Low       Close   Adj Close  \
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  
         Volume  Daily Returns  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  ,
            Date        Open        High         Low       Close   Adj Close  \
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  
         Volume  Daily Returns  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  ,
            Date        Open        High         Low       Close   Adj Close  \
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  
         Volume  Daily Returns  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  ,
            Date        Open        High         Low       Close   Adj Close  \
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  
         Volume  Daily Returns  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  ,
            Date        Open        High         Low       Close   Adj Close  \
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  
         Volume  Daily Returns  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  ,
            Date        Open        High         Low       Close   Adj Close  \
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  
         Volume  Daily Returns  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  ,
            Date        Open        High         Low       Close   Adj Close  \
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  
         Volume  Daily Returns  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  ,
            Date        Open        High         Low       Close   Adj Close  \
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  
         Volume  Daily Returns  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  ,
            Date        Open        High         Low       Close   Adj Close  \
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  
         Volume  Daily Returns  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  ,
            Date        Open        High         Low       Close   Adj Close  \
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  
         Volume  Daily Returns  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  ,
            Date        Open        High         Low       Close   Adj Close  \
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  
         Volume  Daily Returns  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  ,
            Date        Open        High         Low       Close   Adj Close  \
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  
         Volume  Daily Returns  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  ,
            Date        Open        High         Low       Close   Adj Close  \
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  
         Volume  Daily Returns  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  ,
            Date        Open        High         Low       Close   Adj Close  \
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  
         Volume  Daily Returns  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  ,
            Date        Open        High         Low       Close   Adj Close  \
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  
         Volume  Daily Returns  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  ,
            Date        Open        High         Low       Close   Adj Close  \
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  
         Volume  Daily Returns  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  ,
            Date        Open        High         Low       Close   Adj Close  \
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  
         Volume  Daily Returns  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  ,
            Date        Open        High         Low       Close   Adj Close  \
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  
         Volume  Daily Returns  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  ,
            Date        Open        High         Low       Close   Adj Close  \
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  
         Volume  Daily Returns  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  ,
            Date        Open        High         Low       Close   Adj Close  \
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  
         Volume  Daily Returns  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  ,
            Date        Open        High         Low       Close   Adj Close  \
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  
         Volume  Daily Returns  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  ,
            Date        Open        High         Low       Close   Adj Close  \
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  
         Volume  Daily Returns  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  ,
            Date        Open        High         Low       Close   Adj Close  \
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  
         Volume  Daily Returns  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  ,
            Date        Open        High         Low       Close   Adj Close  \
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  
         Volume  Daily Returns  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  ,
            Date        Open        High         Low       Close   Adj Close  \
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  
         Volume  Daily Returns  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  ,
            Date        Open        High         Low       Close   Adj Close  \
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  
         Volume  Daily Returns  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  ,
            Date        Open        High         Low       Close   Adj Close  \
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  
         Volume  Daily Returns  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  ,
            Date        Open        High         Low       Close   Adj Close  \
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  
         Volume  Daily Returns  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  ,
            Date        Open        High         Low       Close   Adj Close  \
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  
         Volume  Daily Returns  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  ,
            Date        Open        High         Low       Close   Adj Close  \
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  
         Volume  Daily Returns  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  ,
            Date        Open        High         Low       Close   Adj Close  \
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  
         Volume  Daily Returns  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  ,
            Date        Open        High         Low       Close   Adj Close  \
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  
         Volume  Daily Returns  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  ,
            Date        Open        High         Low       Close   Adj Close  \
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  
         Volume  Daily Returns  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  ,
            Date        Open        High         Low       Close   Adj Close  \
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  
         Volume  Daily Returns  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  ,
            Date        Open        High         Low       Close   Adj Close  \
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  
         Volume  Daily Returns  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  ,
            Date        Open        High         Low       Close   Adj Close  \
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  
         Volume  Daily Returns  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  ,
            Date        Open        High         Low       Close   Adj Close  \
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  
         Volume  Daily Returns  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  ,
            Date        Open        High         Low       Close   Adj Close  \
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  
         Volume  Daily Returns  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  ,
            Date        Open        High         Low       Close   Adj Close  \
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  
         Volume  Daily Returns  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  ,
            Date        Open        High         Low       Close   Adj Close  \
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  
         Volume  Daily Returns  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  ,
            Date        Open        High         Low       Close   Adj Close  \
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  
         Volume  Daily Returns  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  ,
            Date        Open        High         Low       Close   Adj Close  \
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  
         Volume  Daily Returns  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  ,
            Date        Open        High         Low       Close   Adj Close  \
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  
         Volume  Daily Returns  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  ,
            Date        Open        High         Low       Close   Adj Close  \
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  
         Volume  Daily Returns  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  ,
            Date        Open        High         Low       Close   Adj Close  \
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  
         Volume  Daily Returns  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  ,
            Date        Open        High         Low       Close   Adj Close  \
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  
         Volume  Daily Returns  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  ,
            Date        Open        High         Low       Close   Adj Close  \
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  
         Volume  Daily Returns  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  ,
            Date        Open        High         Low       Close   Adj Close  \
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  
         Volume  Daily Returns  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  ,
            Date        Open        High         Low       Close   Adj Close  \
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  
         Volume  Daily Returns  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  ,
            Date        Open        High         Low       Close   Adj Close  \
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  
         Volume  Daily Returns  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  ,
            Date        Open        High         Low       Close   Adj Close  \
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  
         Volume  Daily Returns  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  ,
            Date        Open        High         Low       Close   Adj Close  \
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  
         Volume  Daily Returns  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  ,
            Date        Open        High         Low       Close   Adj Close  \
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  
         Volume  Daily Returns  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  ,
            Date        Open        High         Low       Close   Adj Close  \
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  
         Volume  Daily Returns  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  ,
            Date        Open        High         Low       Close   Adj Close  \
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  
         Volume  Daily Returns  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  ,
            Date        Open        High         Low       Close   Adj Close  \
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  
         Volume  Daily Returns  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  ,
            Date        Open        High         Low       Close   Adj Close  \
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  
         Volume  Daily Returns  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  ,
            Date        Open        High         Low       Close   Adj Close  \
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  
         Volume  Daily Returns  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  ,
            Date        Open        High         Low       Close   Adj Close  \
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  
         Volume  Daily Returns  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  ,
            Date        Open        High         Low       Close   Adj Close  \
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  
         Volume  Daily Returns  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  ,
            Date        Open        High         Low       Close   Adj Close  \
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  
         Volume  Daily Returns  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  ,
            Date        Open        High         Low       Close   Adj Close  \
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  
         Volume  Daily Returns  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  ,
            Date        Open        High         Low       Close   Adj Close  \
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  
         Volume  Daily Returns  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  ,
            Date        Open        High         Low       Close   Adj Close  \
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  
         Volume  Daily Returns  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  ,
            Date        Open        High         Low       Close   Adj Close  \
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  
         Volume  Daily Returns  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  ,
            Date        Open        High         Low       Close   Adj Close  \
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  
         Volume  Daily Returns  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  ,
            Date        Open        High         Low       Close   Adj Close  \
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  
         Volume  Daily Returns  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  ,
            Date        Open        High         Low       Close   Adj Close  \
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  
         Volume  Daily Returns  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  ,
            Date        Open        High         Low       Close   Adj Close  \
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  
         Volume  Daily Returns  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  ,
            Date        Open        High         Low       Close   Adj Close  \
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  
         Volume  Daily Returns  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  ,
            Date        Open        High         Low       Close   Adj Close  \
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  
         Volume  Daily Returns  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  ,
            Date        Open        High         Low       Close   Adj Close  \
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  
         Volume  Daily Returns  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  ,
            Date        Open        High         Low       Close   Adj Close  \
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  
         Volume  Daily Returns  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  ,
            Date        Open        High         Low       Close   Adj Close  \
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  
         Volume  Daily Returns  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  ,
            Date        Open        High         Low       Close   Adj Close  \
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  
         Volume  Daily Returns  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  ,
            Date        Open        High         Low       Close   Adj Close  \
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  
         Volume  Daily Returns  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  ,
            Date        Open        High         Low       Close   Adj Close  \
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  
         Volume  Daily Returns  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  ,
            Date        Open        High         Low       Close   Adj Close  \
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  
         Volume  Daily Returns  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  ,
            Date        Open        High         Low       Close   Adj Close  \
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  
         Volume  Daily Returns  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  ,
            Date        Open        High         Low       Close   Adj Close  \
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  
         Volume  Daily Returns  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  ,
            Date        Open        High         Low       Close   Adj Close  \
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  
         Volume  Daily Returns  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  ,
            Date        Open        High         Low       Close   Adj Close  \
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  
         Volume  Daily Returns  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  ,
            Date        Open        High         Low       Close   Adj Close  \
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  
         Volume  Daily Returns  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  ,
            Date        Open        High         Low       Close   Adj Close  \
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  
         Volume  Daily Returns  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  ,
            Date        Open        High         Low       Close   Adj Close  \
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  
         Volume  Daily Returns  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  ,
            Date        Open        High         Low       Close   Adj Close  \
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  
         Volume  Daily Returns  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  ,
            Date        Open        High         Low       Close   Adj Close  \
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  
         Volume  Daily Returns  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  ,
            Date        Open        High         Low       Close   Adj Close  \
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  
         Volume  Daily Returns  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  ,
            Date        Open        High         Low       Close   Adj Close  \
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  
         Volume  Daily Returns  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  ,
            Date        Open        High         Low       Close   Adj Close  \
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  
         Volume  Daily Returns  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  ,
            Date        Open        High         Low       Close   Adj Close  \
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  
         Volume  Daily Returns  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  ,
            Date        Open        High         Low       Close   Adj Close  \
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  
         Volume  Daily Returns  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  ,
            Date        Open        High         Low       Close   Adj Close  \
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  
         Volume  Daily Returns  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  ,
            Date        Open        High         Low       Close   Adj Close  \
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  
         Volume  Daily Returns  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  ,
            Date        Open        High         Low       Close   Adj Close  \
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  
         Volume  Daily Returns  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  ,
            Date        Open        High         Low       Close   Adj Close  \
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  
         Volume  Daily Returns  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  ,
            Date        Open        High         Low       Close   Adj Close  \
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  
         Volume  Daily Returns  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  ,
            Date        Open        High         Low       Close   Adj Close  \
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  
         Volume  Daily Returns  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  ,
            Date        Open        High         Low       Close   Adj Close  \
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  
         Volume  Daily Returns  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  ,
            Date        Open        High         Low       Close   Adj Close  \
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  
         Volume  Daily Returns  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  ,
            Date        Open        High         Low       Close   Adj Close  \
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  
         Volume  Daily Returns  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  ,
            Date        Open        High         Low       Close   Adj Close  \
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  
         Volume  Daily Returns  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  ,
            Date        Open        High         Low       Close   Adj Close  \
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  
         Volume  Daily Returns  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  ,
            Date        Open        High         Low       Close   Adj Close  \
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  
         Volume  Daily Returns  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  ,
            Date        Open        High         Low       Close   Adj Close  \
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  
         Volume  Daily Returns  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  ,
            Date        Open        High         Low       Close   Adj Close  \
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  
         Volume  Daily Returns  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  ,
            Date        Open        High         Low       Close   Adj Close  \
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  
         Volume  Daily Returns  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  ,
            Date        Open        High         Low       Close   Adj Close  \
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  
         Volume  Daily Returns  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  ,
            Date        Open        High         Low       Close   Adj Close  \
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  
         Volume  Daily Returns  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  ,
            Date        Open        High         Low       Close   Adj Close  \
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  
         Volume  Daily Returns  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  ,
            Date        Open        High         Low       Close   Adj Close  \
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  
         Volume  Daily Returns  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  ,
            Date        Open        High         Low       Close   Adj Close  \
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  
         Volume  Daily Returns  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  ,
            Date        Open        High         Low       Close   Adj Close  \
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  
         Volume  Daily Returns  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  ,
            Date        Open        High         Low       Close   Adj Close  \
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  
         Volume  Daily Returns  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  ,
            Date        Open        High         Low       Close   Adj Close  \
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  
         Volume  Daily Returns  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  ,
            Date        Open        High         Low       Close   Adj Close  \
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  
         Volume  Daily Returns  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  ,
            Date        Open        High         Low       Close   Adj Close  \
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  
         Volume  Daily Returns  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  ,
            Date        Open        High         Low       Close   Adj Close  \
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  
         Volume  Daily Returns  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  ,
            Date        Open        High         Low       Close   Adj Close  \
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  
         Volume  Daily Returns  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  ,
            Date        Open        High         Low       Close   Adj Close  \
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  
         Volume  Daily Returns  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  ,
            Date        Open        High         Low       Close   Adj Close  \
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  
         Volume  Daily Returns  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  ,
            Date        Open        High         Low       Close   Adj Close  \
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  
         Volume  Daily Returns  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  ,
            Date        Open        High         Low       Close   Adj Close  \
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  
         Volume  Daily Returns  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  ,
            Date        Open        High         Low       Close   Adj Close  \
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  
         Volume  Daily Returns  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  ,
            Date        Open        High         Low       Close   Adj Close  \
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  
         Volume  Daily Returns  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  ,
            Date        Open        High         Low       Close   Adj Close  \
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  
         Volume  Daily Returns  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  ,
            Date        Open        High         Low       Close   Adj Close  \
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  
         Volume  Daily Returns  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  ,
            Date        Open        High         Low       Close   Adj Close  \
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  
         Volume  Daily Returns  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  ,
            Date        Open        High         Low       Close   Adj Close  \
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  
         Volume  Daily Returns  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  ,
            Date        Open        High         Low       Close   Adj Close  \
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  
         Volume  Daily Returns  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  ,
            Date        Open        High         Low       Close   Adj Close  \
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  
         Volume  Daily Returns  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  ,
            Date        Open        High         Low       Close   Adj Close  \
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  
         Volume  Daily Returns  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  ,
            Date        Open        High         Low       Close   Adj Close  \
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  
         Volume  Daily Returns  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  ,
            Date        Open        High         Low       Close   Adj Close  \
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  
         Volume  Daily Returns  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  ,
            Date        Open        High         Low       Close   Adj Close  \
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  
         Volume  Daily Returns  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  ,
            Date        Open        High         Low       Close   Adj Close  \
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  
         Volume  Daily Returns  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  ,
            Date        Open        High         Low       Close   Adj Close  \
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  
         Volume  Daily Returns  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  ,
            Date        Open        High         Low       Close   Adj Close  \
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  
         Volume  Daily Returns  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  ,
            Date        Open        High         Low       Close   Adj Close  \
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  
         Volume  Daily Returns  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  ,
            Date        Open        High         Low       Close   Adj Close  \
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  
         Volume  Daily Returns  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  ,
            Date        Open        High         Low       Close   Adj Close  \
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  
         Volume  Daily Returns  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  ,
            Date        Open        High         Low       Close   Adj Close  \
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  
         Volume  Daily Returns  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  ,
            Date        Open        High         Low       Close   Adj Close  \
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  
         Volume  Daily Returns  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  ,
            Date        Open        High         Low       Close   Adj Close  \
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  
         Volume  Daily Returns  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  ,
            Date        Open        High         Low       Close   Adj Close  \
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  
         Volume  Daily Returns  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  ,
            Date        Open        High         Low       Close   Adj Close  \
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  
         Volume  Daily Returns  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  ,
            Date        Open        High         Low       Close   Adj Close  \
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  
         Volume  Daily Returns  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  ,
            Date        Open        High         Low       Close   Adj Close  \
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  
         Volume  Daily Returns  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  ,
            Date        Open        High         Low       Close   Adj Close  \
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  
         Volume  Daily Returns  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  ,
            Date        Open        High         Low       Close   Adj Close  \
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  
         Volume  Daily Returns  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  ,
            Date        Open        High         Low       Close   Adj Close  \
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  
         Volume  Daily Returns  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  ,
            Date        Open        High         Low       Close   Adj Close  \
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  
         Volume  Daily Returns  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  ,
            Date        Open        High         Low       Close   Adj Close  \
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  
         Volume  Daily Returns  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  ,
            Date        Open        High         Low       Close   Adj Close  \
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  
         Volume  Daily Returns  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  ,
            Date        Open        High         Low       Close   Adj Close  \
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  
         Volume  Daily Returns  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  ,
            Date        Open        High         Low       Close   Adj Close  \
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  
         Volume  Daily Returns  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  ,
            Date        Open        High         Low       Close   Adj Close  \
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  
         Volume  Daily Returns  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  ,
            Date        Open        High         Low       Close   Adj Close  \
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  
         Volume  Daily Returns  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  ,
            Date        Open        High         Low       Close   Adj Close  \
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  
         Volume  Daily Returns  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  ,
            Date        Open        High         Low       Close   Adj Close  \
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  
         Volume  Daily Returns  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  ,
            Date        Open        High         Low       Close   Adj Close  \
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  
         Volume  Daily Returns  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  ,
            Date        Open        High         Low       Close   Adj Close  \
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  
         Volume  Daily Returns  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  ,
            Date        Open        High         Low       Close   Adj Close  \
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  
         Volume  Daily Returns  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  ,
            Date        Open        High         Low       Close   Adj Close  \
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  
         Volume  Daily Returns  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  ,
            Date        Open        High         Low       Close   Adj Close  \
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  
         Volume  Daily Returns  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  ,
            Date        Open        High         Low       Close   Adj Close  \
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  
         Volume  Daily Returns  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  ,
            Date        Open        High         Low       Close   Adj Close  \
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  
         Volume  Daily Returns  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  ,
            Date        Open        High         Low       Close   Adj Close  \
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  
         Volume  Daily Returns  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  ,
            Date        Open        High         Low       Close   Adj Close  \
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  
         Volume  Daily Returns  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  ,
            Date        Open        High         Low       Close   Adj Close  \
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  
         Volume  Daily Returns  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  ,
            Date        Open        High         Low       Close   Adj Close  \
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  
         Volume  Daily Returns  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  ,
            Date        Open        High         Low       Close   Adj Close  \
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  
         Volume  Daily Returns  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  ,
            Date        Open        High         Low       Close   Adj Close  \
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  
         Volume  Daily Returns  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  ,
            Date        Open        High         Low       Close   Adj Close  \
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  
         Volume  Daily Returns  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  ,
            Date        Open        High         Low       Close   Adj Close  \
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  
         Volume  Daily Returns  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  ,
            Date        Open        High         Low       Close   Adj Close  \
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  
         Volume  Daily Returns  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  ,
            Date        Open        High         Low       Close   Adj Close  \
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  
         Volume  Daily Returns  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  ,
            Date        Open        High         Low       Close   Adj Close  \
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  
         Volume  Daily Returns  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  ,
            Date        Open        High         Low       Close   Adj Close  \
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  
         Volume  Daily Returns  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  ,
            Date        Open        High         Low       Close   Adj Close  \
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  
         Volume  Daily Returns  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  ,
            Date        Open        High         Low       Close   Adj Close  \
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  
         Volume  Daily Returns  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  ,
            Date        Open        High         Low       Close   Adj Close  \
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  
         Volume  Daily Returns  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  ,
            Date        Open        High         Low       Close   Adj Close  \
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  
         Volume  Daily Returns  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  ,
            Date        Open        High         Low       Close   Adj Close  \
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  
         Volume  Daily Returns  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  ,
            Date        Open        High         Low       Close   Adj Close  \
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  
         Volume  Daily Returns  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  ,
            Date        Open        High         Low       Close   Adj Close  \
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  
         Volume  Daily Returns  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  ,
            Date        Open        High         Low       Close   Adj Close  \
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  
         Volume  Daily Returns  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  ,
            Date        Open        High         Low       Close   Adj Close  \
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  
         Volume  Daily Returns  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  ,
            Date        Open        High         Low       Close   Adj Close  \
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  
         Volume  Daily Returns  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  ,
            Date        Open        High         Low       Close   Adj Close  \
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  
         Volume  Daily Returns  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  ,
            Date        Open        High         Low       Close   Adj Close  \
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  
         Volume  Daily Returns  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  ,
            Date        Open        High         Low       Close   Adj Close  \
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  
         Volume  Daily Returns  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  ,
            Date        Open        High         Low       Close   Adj Close  \
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  
         Volume  Daily Returns  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  ,
            Date        Open        High         Low       Close   Adj Close  \
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  
         Volume  Daily Returns  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  ,
            Date        Open        High         Low       Close   Adj Close  \
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  
         Volume  Daily Returns  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  ,
            Date        Open        High         Low       Close   Adj Close  \
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  
         Volume  Daily Returns  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  ,
            Date        Open        High         Low       Close   Adj Close  \
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  
         Volume  Daily Returns  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  ,
            Date        Open        High         Low       Close   Adj Close  \
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  
         Volume  Daily Returns  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  ,
            Date        Open        High         Low       Close   Adj Close  \
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  
         Volume  Daily Returns  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  ,
            Date        Open        High         Low       Close   Adj Close  \
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  
         Volume  Daily Returns  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  ,
            Date        Open        High         Low       Close   Adj Close  \
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  
         Volume  Daily Returns  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  ,
            Date        Open        High         Low       Close   Adj Close  \
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  
         Volume  Daily Returns  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  ,
            Date        Open        High         Low       Close   Adj Close  \
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  
         Volume  Daily Returns  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  ,
            Date        Open        High         Low       Close   Adj Close  \
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  
         Volume  Daily Returns  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  ,
            Date        Open        High         Low       Close   Adj Close  \
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  
         Volume  Daily Returns  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  ,
            Date        Open        High         Low       Close   Adj Close  \
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  
         Volume  Daily Returns  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  ,
            Date        Open        High         Low       Close   Adj Close  \
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  
         Volume  Daily Returns  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  ,
            Date        Open        High         Low       Close   Adj Close  \
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  
         Volume  Daily Returns  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  ,
            Date        Open        High         Low       Close   Adj Close  \
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  
         Volume  Daily Returns  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  ,
            Date        Open        High         Low       Close   Adj Close  \
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  
         Volume  Daily Returns  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  ,
            Date        Open        High         Low       Close   Adj Close  \
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  
         Volume  Daily Returns  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  ,
            Date        Open        High         Low       Close   Adj Close  \
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  
         Volume  Daily Returns  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  ,
            Date        Open        High         Low       Close   Adj Close  \
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  
         Volume  Daily Returns  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  ,
            Date        Open        High         Low       Close   Adj Close  \
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  
         Volume  Daily Returns  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  ,
            Date        Open        High         Low       Close   Adj Close  \
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  
         Volume  Daily Returns  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  ,
            Date        Open        High         Low       Close   Adj Close  \
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  
         Volume  Daily Returns  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  ,
            Date        Open        High         Low       Close   Adj Close  \
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  
         Volume  Daily Returns  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  ,
            Date        Open        High         Low       Close   Adj Close  \
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  
         Volume  Daily Returns  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  ,
            Date        Open        High         Low       Close   Adj Close  \
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  
         Volume  Daily Returns  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  ,
            Date        Open        High         Low       Close   Adj Close  \
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  
         Volume  Daily Returns  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  ,
            Date        Open        High         Low       Close   Adj Close  \
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  
         Volume  Daily Returns  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  ,
            Date        Open        High         Low       Close   Adj Close  \
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  
         Volume  Daily Returns  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  ,
            Date        Open        High         Low       Close   Adj Close  \
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  
         Volume  Daily Returns  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  ,
            Date        Open        High         Low       Close   Adj Close  \
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  
         Volume  Daily Returns  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  ,
            Date        Open        High         Low       Close   Adj Close  \
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  
         Volume  Daily Returns  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  ,
            Date        Open        High         Low       Close   Adj Close  \
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  
         Volume  Daily Returns  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  ,
            Date        Open        High         Low       Close   Adj Close  \
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  
         Volume  Daily Returns  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  ,
            Date        Open        High         Low       Close   Adj Close  \
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  
         Volume  Daily Returns  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  ,
            Date        Open        High         Low       Close   Adj Close  \
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  
         Volume  Daily Returns  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  ,
            Date        Open        High         Low       Close   Adj Close  \
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  
         Volume  Daily Returns  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  ,
            Date        Open        High         Low       Close   Adj Close  \
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  
         Volume  Daily Returns  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  ,
            Date        Open        High         Low       Close   Adj Close  \
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  
         Volume  Daily Returns  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  ,
            Date        Open        High         Low       Close   Adj Close  \
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  
         Volume  Daily Returns  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  ,
            Date        Open        High         Low       Close   Adj Close  \
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  
         Volume  Daily Returns  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  ,
            Date        Open        High         Low       Close   Adj Close  \
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  
         Volume  Daily Returns  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  ,
            Date        Open        High         Low       Close   Adj Close  \
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  
         Volume  Daily Returns  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  ,
            Date        Open        High         Low       Close   Adj Close  \
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  
         Volume  Daily Returns  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  ,
            Date        Open        High         Low       Close   Adj Close  \
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  
         Volume  Daily Returns  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  ,
            Date        Open        High         Low       Close   Adj Close  \
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  
         Volume  Daily Returns  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  ,
            Date        Open        High         Low       Close   Adj Close  \
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  
         Volume  Daily Returns  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  ,
            Date        Open        High         Low       Close   Adj Close  \
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  
         Volume  Daily Returns  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  ,
            Date        Open        High         Low       Close   Adj Close  \
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  
         Volume  Daily Returns  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  ,
            Date        Open        High         Low       Close   Adj Close  \
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  
         Volume  Daily Returns  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  ,
            Date        Open        High         Low       Close   Adj Close  \
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  
         Volume  Daily Returns  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  ,
            Date        Open        High         Low       Close   Adj Close  \
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  
         Volume  Daily Returns  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  ,
            Date        Open        High         Low       Close   Adj Close  \
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  
         Volume  Daily Returns  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  ,
            Date        Open        High         Low       Close   Adj Close  \
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  
         Volume  Daily Returns  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  ,
            Date        Open        High         Low       Close   Adj Close  \
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  
         Volume  Daily Returns  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  ,
            Date        Open        High         Low       Close   Adj Close  \
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  
         Volume  Daily Returns  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  ,
            Date        Open        High         Low       Close   Adj Close  \
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  
         Volume  Daily Returns  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  ,
            Date        Open        High         Low       Close   Adj Close  \
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  
         Volume  Daily Returns  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  ,
            Date        Open        High         Low       Close   Adj Close  \
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  
         Volume  Daily Returns  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  ,
            Date        Open        High         Low       Close   Adj Close  \
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  
         Volume  Daily Returns  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  ,
            Date        Open        High         Low       Close   Adj Close  \
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  
         Volume  Daily Returns  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  ,
            Date        Open        High         Low       Close   Adj Close  \
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  
         Volume  Daily Returns  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  ,
            Date        Open        High         Low       Close   Adj Close  \
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  
         Volume  Daily Returns  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  ,
            Date        Open        High         Low       Close   Adj Close  \
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  
         Volume  Daily Returns  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  ,
            Date        Open        High         Low       Close   Adj Close  \
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  
         Volume  Daily Returns  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  ,
            Date        Open        High         Low       Close   Adj Close  \
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  
         Volume  Daily Returns  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  ,
            Date        Open        High         Low       Close   Adj Close  \
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  
         Volume  Daily Returns  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  ,
            Date        Open        High         Low       Close   Adj Close  \
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  
         Volume  Daily Returns  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  ,
            Date        Open        High         Low       Close   Adj Close  \
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  
         Volume  Daily Returns  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  ,
            Date        Open        High         Low       Close   Adj Close  \
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  
         Volume  Daily Returns  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  ,
            Date        Open        High         Low       Close   Adj Close  \
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  
         Volume  Daily Returns  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  ,
            Date        Open        High         Low       Close   Adj Close  \
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  
         Volume  Daily Returns  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  ,
            Date        Open        High         Low       Close   Adj Close  \
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  
         Volume  Daily Returns  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  ,
            Date        Open        High         Low       Close   Adj Close  \
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  
         Volume  Daily Returns  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  ,
            Date        Open        High         Low       Close   Adj Close  \
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  
         Volume  Daily Returns  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  ,
            Date        Open        High         Low       Close   Adj Close  \
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  
         Volume  Daily Returns  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  ,
            Date        Open        High         Low       Close   Adj Close  \
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  
         Volume  Daily Returns  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  ,
            Date        Open        High         Low       Close   Adj Close  \
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  
         Volume  Daily Returns  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  
  539  97743000      -0.027192  ,
            Date        Open        High         Low       Close   Adj Close  \
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  
         Volume  Daily Returns  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  
  539  97743000      -0.027192  
  540  79537700       0.005154  ,
            Date        Open        High         Low       Close   Adj Close  \
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  
          Volume  Daily Returns  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  ,
            Date        Open        High         Low       Close   Adj Close  \
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  
          Volume  Daily Returns  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  ,
            Date        Open        High         Low       Close   Adj Close  \
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  
          Volume  Daily Returns  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  ,
            Date        Open        High         Low       Close   Adj Close  \
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  
          Volume  Daily Returns  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  ,
            Date        Open        High         Low       Close   Adj Close  \
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  
          Volume  Daily Returns  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  ,
            Date        Open        High         Low       Close   Adj Close  \
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  
          Volume  Daily Returns  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  ,
            Date        Open        High         Low       Close   Adj Close  \
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  
          Volume  Daily Returns  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  ,
            Date        Open        High         Low       Close   Adj Close  \
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  
          Volume  Daily Returns  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  ,
            Date        Open        High         Low       Close   Adj Close  \
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  
          Volume  Daily Returns  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  ,
            Date        Open        High         Low       Close   Adj Close  \
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  
          Volume  Daily Returns  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  ,
            Date        Open        High         Low       Close   Adj Close  \
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  
          Volume  Daily Returns  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  ,
            Date        Open        High         Low       Close   Adj Close  \
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  
          Volume  Daily Returns  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  ,
            Date        Open        High         Low       Close   Adj Close  \
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  
          Volume  Daily Returns  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  ,
            Date        Open        High         Low       Close   Adj Close  \
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  
          Volume  Daily Returns  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  ,
            Date        Open        High         Low       Close   Adj Close  \
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  
          Volume  Daily Returns  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  ,
            Date        Open        High         Low       Close   Adj Close  \
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  
          Volume  Daily Returns  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  ,
            Date        Open        High         Low       Close   Adj Close  \
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  
          Volume  Daily Returns  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  ,
            Date        Open        High         Low       Close   Adj Close  \
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  
          Volume  Daily Returns  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  ,
            Date        Open        High         Low       Close   Adj Close  \
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  
          Volume  Daily Returns  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  ,
            Date        Open        High         Low       Close   Adj Close  \
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  
          Volume  Daily Returns  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  ,
            Date        Open        High         Low       Close   Adj Close  \
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  
          Volume  Daily Returns  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  ,
            Date        Open        High         Low       Close   Adj Close  \
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  
          Volume  Daily Returns  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  ,
            Date        Open        High         Low       Close   Adj Close  \
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  
         Volume  Daily Returns  
  559  94881800       0.077437  
  560  88754900      -0.007405  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  ,
            Date        Open        High         Low       Close   Adj Close  \
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  
         Volume  Daily Returns  
  560  88754900      -0.007405  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  ,
            Date        Open        High         Low       Close   Adj Close  \
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  
         Volume  Daily Returns  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  ,
            Date        Open        High         Low       Close   Adj Close  \
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  
         Volume  Daily Returns  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  ,
            Date        Open        High         Low       Close   Adj Close  \
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  
         Volume  Daily Returns  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  ,
            Date        Open        High         Low       Close   Adj Close  \
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  
         Volume  Daily Returns  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  ,
            Date        Open        High         Low       Close   Adj Close  \
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  
         Volume  Daily Returns  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  ,
            Date        Open        High         Low       Close   Adj Close  \
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  
         Volume  Daily Returns  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  ,
            Date        Open        High         Low       Close   Adj Close  \
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  
         Volume  Daily Returns  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  ,
            Date        Open        High         Low       Close   Adj Close  \
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  
         Volume  Daily Returns  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  ,
            Date        Open        High         Low       Close   Adj Close  \
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  
         Volume  Daily Returns  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  ,
            Date        Open        High         Low       Close   Adj Close  \
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  
         Volume  Daily Returns  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  ,
            Date        Open        High         Low       Close   Adj Close  \
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  
         Volume  Daily Returns  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  ,
            Date        Open        High         Low       Close   Adj Close  \
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  
         Volume  Daily Returns  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  ,
            Date        Open        High         Low       Close   Adj Close  \
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  
         Volume  Daily Returns  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  ,
            Date        Open        High         Low       Close   Adj Close  \
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  
         Volume  Daily Returns  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  ,
            Date        Open        High         Low       Close   Adj Close  \
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  
         Volume  Daily Returns  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  ,
            Date        Open        High         Low       Close   Adj Close  \
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  
         Volume  Daily Returns  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  ,
            Date        Open        High         Low       Close   Adj Close  \
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  
         Volume  Daily Returns  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  ,
            Date        Open        High         Low       Close   Adj Close  \
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  
         Volume  Daily Returns  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  ,
            Date        Open        High         Low       Close   Adj Close  \
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  
         Volume  Daily Returns  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  ,
            Date        Open        High         Low       Close   Adj Close  \
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  
         Volume  Daily Returns  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  ,
            Date        Open        High         Low       Close   Adj Close  \
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  
         Volume  Daily Returns  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  ,
            Date        Open        High         Low       Close   Adj Close  \
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  
         Volume  Daily Returns  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  ,
            Date        Open        High         Low       Close   Adj Close  \
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  
         Volume  Daily Returns  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  ,
            Date        Open        High         Low       Close   Adj Close  \
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  
         Volume  Daily Returns  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  ,
            Date        Open        High         Low       Close   Adj Close  \
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  
         Volume  Daily Returns  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  ,
            Date        Open        High         Low       Close   Adj Close  \
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  
         Volume  Daily Returns  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  ,
            Date        Open        High         Low       Close   Adj Close  \
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  
         Volume  Daily Returns  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  ,
            Date        Open        High         Low       Close   Adj Close  \
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  
         Volume  Daily Returns  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  ,
            Date        Open        High         Low       Close   Adj Close  \
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  
         Volume  Daily Returns  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  ,
            Date        Open        High         Low       Close   Adj Close  \
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  
         Volume  Daily Returns  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  ,
            Date        Open        High         Low       Close   Adj Close  \
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  
         Volume  Daily Returns  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  ,
            Date        Open        High         Low       Close   Adj Close  \
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  
         Volume  Daily Returns  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  ,
            Date        Open        High         Low       Close   Adj Close  \
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  
         Volume  Daily Returns  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  ,
            Date        Open        High         Low       Close   Adj Close  \
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  
         Volume  Daily Returns  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  ,
            Date        Open        High         Low       Close   Adj Close  \
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  
         Volume  Daily Returns  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  ,
            Date        Open        High         Low       Close   Adj Close  \
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  
         Volume  Daily Returns  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  ,
            Date        Open        High         Low       Close   Adj Close  \
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  
         Volume  Daily Returns  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  ,
            Date        Open        High         Low       Close   Adj Close  \
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  
         Volume  Daily Returns  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  ,
            Date        Open        High         Low       Close   Adj Close  \
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  
         Volume  Daily Returns  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  ,
            Date        Open        High         Low       Close   Adj Close  \
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  
         Volume  Daily Returns  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  ,
            Date        Open        High         Low       Close   Adj Close  \
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  
         Volume  Daily Returns  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  ,
            Date        Open        High         Low       Close   Adj Close  \
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  
         Volume  Daily Returns  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  ,
            Date        Open        High         Low       Close   Adj Close  \
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  
         Volume  Daily Returns  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  ,
            Date        Open        High         Low       Close   Adj Close  \
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  
         Volume  Daily Returns  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  ,
            Date        Open        High         Low       Close   Adj Close  \
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  
         Volume  Daily Returns  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  ,
            Date        Open        High         Low       Close   Adj Close  \
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  
         Volume  Daily Returns  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  ,
            Date        Open        High         Low       Close   Adj Close  \
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  
         Volume  Daily Returns  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  ,
            Date        Open        High         Low       Close   Adj Close  \
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  
         Volume  Daily Returns  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  ,
            Date        Open        High         Low       Close   Adj Close  \
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  
         Volume  Daily Returns  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  ,
            Date        Open        High         Low       Close   Adj Close  \
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  
         Volume  Daily Returns  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  ,
            Date        Open        High         Low       Close   Adj Close  \
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  
         Volume  Daily Returns  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  ,
            Date        Open        High         Low       Close   Adj Close  \
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  
         Volume  Daily Returns  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  ,
            Date        Open        High         Low       Close   Adj Close  \
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  
         Volume  Daily Returns  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  ,
            Date        Open        High         Low       Close   Adj Close  \
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  
         Volume  Daily Returns  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  ,
            Date        Open        High         Low       Close   Adj Close  \
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  
         Volume  Daily Returns  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  ,
            Date        Open        High         Low       Close   Adj Close  \
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  
         Volume  Daily Returns  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  ,
            Date        Open        High         Low       Close   Adj Close  \
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  
         Volume  Daily Returns  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  ,
            Date        Open        High         Low       Close   Adj Close  \
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  
         Volume  Daily Returns  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  ,
            Date        Open        High         Low       Close   Adj Close  \
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  
         Volume  Daily Returns  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  ,
            Date        Open        High         Low       Close   Adj Close  \
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  
         Volume  Daily Returns  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  ,
            Date        Open        High         Low       Close   Adj Close  \
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  
         Volume  Daily Returns  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  ,
            Date        Open        High         Low       Close   Adj Close  \
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  
         Volume  Daily Returns  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  ,
            Date        Open        High         Low       Close   Adj Close  \
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  
         Volume  Daily Returns  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  ,
            Date        Open        High         Low       Close   Adj Close  \
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  
         Volume  Daily Returns  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  ,
            Date        Open        High         Low       Close   Adj Close  \
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  
         Volume  Daily Returns  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  ,
            Date        Open        High         Low       Close   Adj Close  \
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  
         Volume  Daily Returns  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  ,
            Date        Open        High         Low       Close   Adj Close  \
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  
         Volume  Daily Returns  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  ,
            Date        Open        High         Low       Close   Adj Close  \
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  
         Volume  Daily Returns  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  ,
            Date        Open        High         Low       Close   Adj Close  \
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  
         Volume  Daily Returns  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  ,
            Date        Open        High         Low       Close   Adj Close  \
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  
         Volume  Daily Returns  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  ,
            Date        Open        High         Low       Close   Adj Close  \
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  
         Volume  Daily Returns  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  ,
            Date        Open        High         Low       Close   Adj Close  \
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  
         Volume  Daily Returns  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  ,
            Date        Open        High         Low       Close   Adj Close  \
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  
         Volume  Daily Returns  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  ,
            Date        Open        High         Low       Close   Adj Close  \
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  
         Volume  Daily Returns  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  ,
            Date        Open        High         Low       Close   Adj Close  \
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  
         Volume  Daily Returns  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  ,
            Date        Open        High         Low       Close   Adj Close  \
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  
         Volume  Daily Returns  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  ,
            Date        Open        High         Low       Close   Adj Close  \
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  
         Volume  Daily Returns  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  ,
            Date        Open        High         Low       Close   Adj Close  \
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  
         Volume  Daily Returns  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  ,
            Date        Open        High         Low       Close   Adj Close  \
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  
         Volume  Daily Returns  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  ,
            Date        Open        High         Low       Close   Adj Close  \
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  
         Volume  Daily Returns  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  ,
            Date        Open        High         Low       Close   Adj Close  \
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  
         Volume  Daily Returns  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  ,
            Date        Open        High         Low       Close   Adj Close  \
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  
         Volume  Daily Returns  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  ,
            Date        Open        High         Low       Close   Adj Close  \
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  
         Volume  Daily Returns  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  ,
            Date        Open        High         Low       Close   Adj Close  \
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  
         Volume  Daily Returns  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  ,
            Date        Open        High         Low       Close   Adj Close  \
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  
         Volume  Daily Returns  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  ,
            Date        Open        High         Low       Close   Adj Close  \
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  
         Volume  Daily Returns  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  ,
            Date        Open        High         Low       Close   Adj Close  \
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  
         Volume  Daily Returns  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  ,
            Date        Open        High         Low       Close   Adj Close  \
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  
         Volume  Daily Returns  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  ,
            Date        Open        High         Low       Close   Adj Close  \
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  
         Volume  Daily Returns  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  ,
            Date        Open        High         Low       Close   Adj Close  \
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  
         Volume  Daily Returns  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  ,
            Date        Open        High         Low       Close   Adj Close  \
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  
         Volume  Daily Returns  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  ,
            Date        Open        High         Low       Close   Adj Close  \
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  
         Volume  Daily Returns  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  ,
            Date        Open        High         Low       Close   Adj Close  \
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  
         Volume  Daily Returns  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  ,
            Date        Open        High         Low       Close   Adj Close  \
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  
         Volume  Daily Returns  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  ,
            Date        Open        High         Low       Close   Adj Close  \
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  
         Volume  Daily Returns  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  ,
            Date        Open        High         Low       Close   Adj Close  \
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  
         Volume  Daily Returns  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  ,
            Date        Open        High         Low       Close   Adj Close  \
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  
         Volume  Daily Returns  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  ,
            Date        Open        High         Low       Close   Adj Close  \
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  
         Volume  Daily Returns  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  ,
            Date        Open        High         Low       Close   Adj Close  \
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  
         Volume  Daily Returns  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  ,
            Date        Open        High         Low       Close   Adj Close  \
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  
         Volume  Daily Returns  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  ,
            Date        Open        High         Low       Close   Adj Close  \
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  
         Volume  Daily Returns  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  ,
            Date        Open        High         Low       Close   Adj Close  \
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  
         Volume  Daily Returns  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  ,
            Date        Open        High         Low       Close   Adj Close  \
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  
         Volume  Daily Returns  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  ,
            Date        Open        High         Low       Close   Adj Close  \
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  
         Volume  Daily Returns  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  ,
            Date        Open        High         Low       Close   Adj Close  \
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  
         Volume  Daily Returns  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  ,
            Date        Open        High         Low       Close   Adj Close  \
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  
         Volume  Daily Returns  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  ,
            Date        Open        High         Low       Close   Adj Close  \
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  
         Volume  Daily Returns  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  
  671  36216200       0.017092  ,
            Date        Open        High         Low       Close   Adj Close  \
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  
         Volume  Daily Returns  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  
  671  36216200       0.017092  
  672  50836800       0.009469  ,
            Date        Open        High         Low       Close   Adj Close  \
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  
          Volume  Daily Returns  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  ,
            Date        Open        High         Low       Close   Adj Close  \
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  
          Volume  Daily Returns  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  ,
            Date        Open        High         Low       Close   Adj Close  \
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  
          Volume  Daily Returns  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  ,
            Date        Open        High         Low       Close   Adj Close  \
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  
          Volume  Daily Returns  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  ,
            Date        Open        High         Low       Close   Adj Close  \
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  
          Volume  Daily Returns  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  ,
            Date        Open        High         Low       Close   Adj Close  \
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  
          Volume  Daily Returns  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  ,
            Date        Open        High         Low       Close   Adj Close  \
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  
         Volume  Daily Returns  
  675  99568600      -0.048064  
  676  64837900       0.029376  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  ,
            Date        Open        High         Low       Close   Adj Close  \
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  
         Volume  Daily Returns  
  676  64837900       0.029376  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  ,
            Date        Open        High         Low       Close   Adj Close  \
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  
         Volume  Daily Returns  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  ,
            Date        Open        High         Low       Close   Adj Close  \
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  
         Volume  Daily Returns  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  ,
            Date        Open        High         Low       Close   Adj Close  \
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  
         Volume  Daily Returns  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  ,
            Date        Open        High         Low       Close   Adj Close  \
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  
         Volume  Daily Returns  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  ,
            Date        Open        High         Low       Close   Adj Close  \
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  
         Volume  Daily Returns  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  ,
            Date        Open        High         Low       Close   Adj Close  \
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  
         Volume  Daily Returns  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  ,
            Date        Open        High         Low       Close   Adj Close  \
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  
         Volume  Daily Returns  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  ,
            Date        Open        High         Low       Close   Adj Close  \
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  
         Volume  Daily Returns  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  ,
            Date        Open        High         Low       Close   Adj Close  \
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  
         Volume  Daily Returns  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  ,
            Date        Open        High         Low       Close   Adj Close  \
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  
         Volume  Daily Returns  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  ,
            Date        Open        High         Low       Close   Adj Close  \
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  
         Volume  Daily Returns  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  ,
            Date        Open        High         Low       Close   Adj Close  \
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  
         Volume  Daily Returns  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  ,
            Date        Open        High         Low       Close   Adj Close  \
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  
         Volume  Daily Returns  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  ,
            Date        Open        High         Low       Close   Adj Close  \
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  
         Volume  Daily Returns  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  ,
            Date        Open        High         Low       Close   Adj Close  \
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  
         Volume  Daily Returns  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  ,
            Date        Open        High         Low       Close   Adj Close  \
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  
         Volume  Daily Returns  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  ,
            Date        Open        High         Low       Close   Adj Close  \
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  
         Volume  Daily Returns  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  ,
            Date        Open        High         Low       Close   Adj Close  \
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  
         Volume  Daily Returns  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  ,
            Date        Open        High         Low       Close   Adj Close  \
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  
         Volume  Daily Returns  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  ,
            Date        Open        High         Low       Close   Adj Close  \
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  
         Volume  Daily Returns  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  ,
            Date        Open        High         Low       Close   Adj Close  \
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  
         Volume  Daily Returns  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  ,
            Date        Open        High         Low       Close   Adj Close  \
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  
         Volume  Daily Returns  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  ,
            Date        Open        High         Low       Close   Adj Close  \
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  
         Volume  Daily Returns  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  ,
            Date        Open        High         Low       Close   Adj Close  \
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  
         Volume  Daily Returns  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  ,
            Date        Open        High         Low       Close   Adj Close  \
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  
         Volume  Daily Returns  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  ,
            Date        Open        High         Low       Close   Adj Close  \
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  
         Volume  Daily Returns  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  ,
            Date        Open        High         Low       Close   Adj Close  \
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  
         Volume  Daily Returns  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  ,
            Date        Open        High         Low       Close   Adj Close  \
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  
         Volume  Daily Returns  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  ,
            Date        Open        High         Low       Close   Adj Close  \
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  
         Volume  Daily Returns  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  ,
            Date        Open        High         Low       Close   Adj Close  \
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  
         Volume  Daily Returns  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  ,
            Date        Open        High         Low       Close   Adj Close  \
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  
         Volume  Daily Returns  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  ,
            Date        Open        High         Low       Close   Adj Close  \
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  
         Volume  Daily Returns  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  ,
            Date        Open        High         Low       Close   Adj Close  \
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  
         Volume  Daily Returns  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  ,
            Date        Open        High         Low       Close   Adj Close  \
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  
         Volume  Daily Returns  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  ,
            Date        Open        High         Low       Close   Adj Close  \
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  
         Volume  Daily Returns  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  ,
            Date        Open        High         Low       Close   Adj Close  \
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  
         Volume  Daily Returns  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  ,
            Date        Open        High         Low       Close   Adj Close  \
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  
         Volume  Daily Returns  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  ,
            Date        Open        High         Low       Close   Adj Close  \
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  
         Volume  Daily Returns  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  ,
            Date        Open        High         Low       Close   Adj Close  \
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  
         Volume  Daily Returns  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  ,
            Date        Open        High         Low       Close   Adj Close  \
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  
         Volume  Daily Returns  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  ,
            Date        Open        High         Low       Close   Adj Close  \
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  
         Volume  Daily Returns  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  ,
            Date        Open        High         Low       Close   Adj Close  \
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  
         Volume  Daily Returns  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  ,
            Date        Open        High         Low       Close   Adj Close  \
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  
         Volume  Daily Returns  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  ,
            Date        Open        High         Low       Close   Adj Close  \
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  
         Volume  Daily Returns  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  ,
            Date        Open        High         Low       Close   Adj Close  \
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  
         Volume  Daily Returns  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  ,
            Date        Open        High         Low       Close   Adj Close  \
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  
         Volume  Daily Returns  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  ,
            Date        Open        High         Low       Close   Adj Close  \
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  
         Volume  Daily Returns  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  ,
            Date        Open        High         Low       Close   Adj Close  \
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  
         Volume  Daily Returns  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  ,
            Date        Open        High         Low       Close   Adj Close  \
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  
         Volume  Daily Returns  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  ,
            Date        Open        High         Low       Close   Adj Close  \
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  
         Volume  Daily Returns  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  ,
            Date        Open        High         Low       Close   Adj Close  \
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  
         Volume  Daily Returns  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  ,
            Date        Open        High         Low       Close   Adj Close  \
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  
         Volume  Daily Returns  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  ,
            Date        Open        High         Low       Close   Adj Close  \
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  
         Volume  Daily Returns  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  ,
            Date        Open        High         Low       Close   Adj Close  \
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  
         Volume  Daily Returns  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  ,
            Date        Open        High         Low       Close   Adj Close  \
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  
         Volume  Daily Returns  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  ,
            Date        Open        High         Low       Close   Adj Close  \
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  
         Volume  Daily Returns  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  ,
            Date        Open        High         Low       Close   Adj Close  \
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  
         Volume  Daily Returns  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  ,
            Date        Open        High         Low       Close   Adj Close  \
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  
         Volume  Daily Returns  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  ,
            Date        Open        High         Low       Close   Adj Close  \
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  
         Volume  Daily Returns  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  ,
            Date        Open        High         Low       Close   Adj Close  \
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  
         Volume  Daily Returns  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  ,
            Date        Open        High         Low       Close   Adj Close  \
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  
         Volume  Daily Returns  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  ,
            Date        Open        High         Low       Close   Adj Close  \
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  
         Volume  Daily Returns  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  ,
            Date        Open        High         Low       Close   Adj Close  \
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  
         Volume  Daily Returns  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  ,
            Date        Open        High         Low       Close   Adj Close  \
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  
         Volume  Daily Returns  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  ,
            Date        Open        High         Low       Close   Adj Close  \
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  
         Volume  Daily Returns  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  ,
            Date        Open        High         Low       Close   Adj Close  \
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  
         Volume  Daily Returns  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  ,
            Date        Open        High         Low       Close   Adj Close  \
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  
         Volume  Daily Returns  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  ,
            Date        Open        High         Low       Close   Adj Close  \
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  
         Volume  Daily Returns  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  ,
            Date        Open        High         Low       Close   Adj Close  \
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  
         Volume  Daily Returns  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  ,
            Date        Open        High         Low       Close   Adj Close  \
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  
         Volume  Daily Returns  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  ,
            Date        Open        High         Low       Close   Adj Close  \
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  
         Volume  Daily Returns  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  ,
            Date        Open        High         Low       Close   Adj Close  \
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  
         Volume  Daily Returns  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  ,
            Date        Open        High         Low       Close   Adj Close  \
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  
         Volume  Daily Returns  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  ,
            Date        Open        High         Low       Close   Adj Close  \
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  
         Volume  Daily Returns  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  ,
            Date        Open        High         Low       Close   Adj Close  \
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  
         Volume  Daily Returns  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  ,
            Date        Open        High         Low       Close   Adj Close  \
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  
         Volume  Daily Returns  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  ,
            Date        Open        High         Low       Close   Adj Close  \
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  
         Volume  Daily Returns  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  ,
            Date        Open        High         Low       Close   Adj Close  \
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  
         Volume  Daily Returns  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  ,
            Date        Open        High         Low       Close   Adj Close  \
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  
         Volume  Daily Returns  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  ,
            Date        Open        High         Low       Close   Adj Close  \
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  
         Volume  Daily Returns  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  ,
            Date        Open        High         Low       Close   Adj Close  \
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  
         Volume  Daily Returns  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  ,
            Date        Open        High         Low       Close   Adj Close  \
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  
         Volume  Daily Returns  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  ,
            Date        Open        High         Low       Close   Adj Close  \
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  
         Volume  Daily Returns  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  ,
            Date        Open        High         Low       Close   Adj Close  \
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  
         Volume  Daily Returns  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  ,
            Date        Open        High         Low       Close   Adj Close  \
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  
         Volume  Daily Returns  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  ,
            Date        Open        High         Low       Close   Adj Close  \
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  
         Volume  Daily Returns  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  ,
            Date        Open        High         Low       Close   Adj Close  \
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  
         Volume  Daily Returns  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  ,
            Date        Open        High         Low       Close   Adj Close  \
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  
         Volume  Daily Returns  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  ,
            Date        Open        High         Low       Close   Adj Close  \
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  
         Volume  Daily Returns  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  ,
            Date        Open        High         Low       Close   Adj Close  \
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  
         Volume  Daily Returns  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  ,
            Date        Open        High         Low       Close   Adj Close  \
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  
         Volume  Daily Returns  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  ,
            Date        Open        High         Low       Close   Adj Close  \
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  
         Volume  Daily Returns  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  ,
            Date        Open        High         Low       Close   Adj Close  \
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  
         Volume  Daily Returns  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  ,
            Date        Open        High         Low       Close   Adj Close  \
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  
         Volume  Daily Returns  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  ,
            Date        Open        High         Low       Close   Adj Close  \
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  
         Volume  Daily Returns  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  ,
            Date        Open        High         Low       Close   Adj Close  \
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  
         Volume  Daily Returns  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  ,
            Date        Open        High         Low       Close   Adj Close  \
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  
         Volume  Daily Returns  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  ,
            Date        Open        High         Low       Close   Adj Close  \
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  
         Volume  Daily Returns  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  ,
            Date        Open        High         Low       Close   Adj Close  \
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  
         Volume  Daily Returns  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  ,
            Date        Open        High         Low       Close   Adj Close  \
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  
         Volume  Daily Returns  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  ,
            Date        Open        High         Low       Close   Adj Close  \
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  
         Volume  Daily Returns  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  ,
            Date        Open        High         Low       Close   Adj Close  \
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  
         Volume  Daily Returns  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  ,
            Date        Open        High         Low       Close   Adj Close  \
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  
         Volume  Daily Returns  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  ,
            Date        Open        High         Low       Close   Adj Close  \
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  
         Volume  Daily Returns  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  ,
            Date        Open        High         Low       Close   Adj Close  \
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  
         Volume  Daily Returns  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  ,
            Date        Open        High         Low       Close   Adj Close  \
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  
         Volume  Daily Returns  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  ,
            Date        Open        High         Low       Close   Adj Close  \
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  
         Volume  Daily Returns  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  ,
            Date        Open        High         Low       Close   Adj Close  \
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  
         Volume  Daily Returns  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  ,
            Date        Open        High         Low       Close   Adj Close  \
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  
         Volume  Daily Returns  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  ,
            Date        Open        High         Low       Close   Adj Close  \
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  
         Volume  Daily Returns  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  
  790  97241900      -0.002977  ,
            Date        Open        High         Low       Close   Adj Close  \
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  
         Volume  Daily Returns  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  
  790  97241900      -0.002977  
  791  58206300       0.008243  ,
            Date        Open        High         Low       Close   Adj Close  \
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  
          Volume  Daily Returns  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  ,
            Date        Open        High         Low       Close   Adj Close  \
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  
          Volume  Daily Returns  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  ,
            Date        Open        High         Low       Close   Adj Close  \
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  
          Volume  Daily Returns  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  ,
            Date        Open        High         Low       Close   Adj Close  \
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  
          Volume  Daily Returns  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  ,
            Date        Open        High         Low       Close   Adj Close  \
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  
          Volume  Daily Returns  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  ,
            Date        Open        High         Low       Close   Adj Close  \
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  
          Volume  Daily Returns  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  ,
            Date        Open        High         Low       Close   Adj Close  \
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  
          Volume  Daily Returns  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  ,
            Date        Open        High         Low       Close   Adj Close  \
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  
          Volume  Daily Returns  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  ,
            Date        Open        High         Low       Close   Adj Close  \
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  
          Volume  Daily Returns  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  ,
            Date        Open        High         Low       Close   Adj Close  \
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  
          Volume  Daily Returns  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  ,
            Date        Open        High         Low       Close   Adj Close  \
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  
          Volume  Daily Returns  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  ,
            Date        Open        High         Low       Close   Adj Close  \
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  
         Volume  Daily Returns  
  799  88409800      -0.028314  
  800  80391100       0.039441  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  ,
            Date        Open        High         Low       Close   Adj Close  \
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  
         Volume  Daily Returns  
  800  80391100       0.039441  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  ,
            Date        Open        High         Low       Close   Adj Close  \
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  
         Volume  Daily Returns  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  ,
            Date        Open        High         Low       Close   Adj Close  \
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  
         Volume  Daily Returns  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  ,
            Date        Open        High         Low       Close   Adj Close  \
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  
         Volume  Daily Returns  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  ,
            Date        Open        High         Low       Close   Adj Close  \
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  
         Volume  Daily Returns  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  ,
            Date        Open        High         Low       Close   Adj Close  \
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  
         Volume  Daily Returns  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  ,
            Date        Open        High         Low       Close   Adj Close  \
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  
         Volume  Daily Returns  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  ,
            Date        Open        High         Low       Close   Adj Close  \
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  
         Volume  Daily Returns  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  ,
            Date        Open        High         Low       Close   Adj Close  \
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  
         Volume  Daily Returns  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  ,
            Date        Open        High         Low       Close   Adj Close  \
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  
         Volume  Daily Returns  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  ,
            Date        Open        High         Low       Close   Adj Close  \
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  
         Volume  Daily Returns  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  ,
            Date        Open        High         Low       Close   Adj Close  \
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  
         Volume  Daily Returns  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  ,
            Date        Open        High         Low       Close   Adj Close  \
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  
         Volume  Daily Returns  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  ,
            Date        Open        High         Low       Close   Adj Close  \
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  
         Volume  Daily Returns  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  ,
            Date        Open        High         Low       Close   Adj Close  \
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  
         Volume  Daily Returns  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  ,
            Date        Open        High         Low       Close   Adj Close  \
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  
         Volume  Daily Returns  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  ,
            Date        Open        High         Low       Close   Adj Close  \
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  
         Volume  Daily Returns  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  ,
            Date        Open        High         Low       Close   Adj Close  \
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  
         Volume  Daily Returns  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  ,
            Date        Open        High         Low       Close   Adj Close  \
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  
         Volume  Daily Returns  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  ,
            Date        Open        High         Low       Close   Adj Close  \
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  
         Volume  Daily Returns  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  ,
            Date        Open        High         Low       Close   Adj Close  \
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  
         Volume  Daily Returns  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  ,
            Date        Open        High         Low       Close   Adj Close  \
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  
         Volume  Daily Returns  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  ,
            Date        Open        High         Low       Close   Adj Close  \
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  
         Volume  Daily Returns  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  ,
            Date        Open        High         Low       Close   Adj Close  \
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  
         Volume  Daily Returns  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  ,
            Date        Open        High         Low       Close   Adj Close  \
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  
         Volume  Daily Returns  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  ,
            Date        Open        High         Low       Close   Adj Close  \
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  
         Volume  Daily Returns  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  ,
            Date        Open        High         Low       Close   Adj Close  \
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  
         Volume  Daily Returns  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  ,
            Date        Open        High         Low       Close   Adj Close  \
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  
         Volume  Daily Returns  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  ,
            Date        Open        High         Low       Close   Adj Close  \
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  
         Volume  Daily Returns  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  ,
            Date        Open        High         Low       Close   Adj Close  \
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  
         Volume  Daily Returns  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  ,
            Date        Open        High         Low       Close   Adj Close  \
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  
         Volume  Daily Returns  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  ,
            Date        Open        High         Low       Close   Adj Close  \
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  
         Volume  Daily Returns  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  ,
            Date        Open        High         Low       Close   Adj Close  \
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  
         Volume  Daily Returns  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  ,
            Date        Open        High         Low       Close   Adj Close  \
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  
         Volume  Daily Returns  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  ,
            Date        Open        High         Low       Close   Adj Close  \
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  
         Volume  Daily Returns  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  ,
            Date        Open        High         Low       Close   Adj Close  \
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  
         Volume  Daily Returns  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  ,
            Date        Open        High         Low       Close   Adj Close  \
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  
         Volume  Daily Returns  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  ,
            Date        Open        High         Low       Close   Adj Close  \
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  
         Volume  Daily Returns  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  ,
            Date        Open        High         Low       Close   Adj Close  \
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  
         Volume  Daily Returns  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  ,
            Date        Open        High         Low       Close   Adj Close  \
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  
         Volume  Daily Returns  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  ,
            Date        Open        High         Low       Close   Adj Close  \
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  
         Volume  Daily Returns  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  ,
            Date        Open        High         Low       Close   Adj Close  \
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  
         Volume  Daily Returns  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  ,
            Date        Open        High         Low       Close   Adj Close  \
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  
         Volume  Daily Returns  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  ,
            Date        Open        High         Low       Close   Adj Close  \
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  
         Volume  Daily Returns  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  ,
            Date        Open        High         Low       Close   Adj Close  \
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  
         Volume  Daily Returns  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  ,
            Date        Open        High         Low       Close   Adj Close  \
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  
         Volume  Daily Returns  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  ,
            Date        Open        High         Low       Close   Adj Close  \
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  
         Volume  Daily Returns  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  ,
            Date        Open        High         Low       Close   Adj Close  \
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  
         Volume  Daily Returns  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  ,
            Date        Open        High         Low       Close   Adj Close  \
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  
         Volume  Daily Returns  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  ,
            Date        Open        High         Low       Close   Adj Close  \
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  
         Volume  Daily Returns  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  ,
            Date        Open        High         Low       Close   Adj Close  \
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  
         Volume  Daily Returns  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  ,
            Date        Open        High         Low       Close   Adj Close  \
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  
         Volume  Daily Returns  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  ,
            Date        Open        High         Low       Close   Adj Close  \
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  
         Volume  Daily Returns  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  ,
            Date        Open        High         Low       Close   Adj Close  \
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  
         Volume  Daily Returns  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  ,
            Date        Open        High         Low       Close   Adj Close  \
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  
         Volume  Daily Returns  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  ,
            Date        Open        High         Low       Close   Adj Close  \
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  
         Volume  Daily Returns  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  ,
            Date        Open        High         Low       Close   Adj Close  \
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  
         Volume  Daily Returns  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  ,
            Date        Open        High         Low       Close   Adj Close  \
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  
         Volume  Daily Returns  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  ,
            Date        Open        High         Low       Close   Adj Close  \
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  
         Volume  Daily Returns  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  ,
            Date        Open        High         Low       Close   Adj Close  \
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  
         Volume  Daily Returns  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  ,
            Date        Open        High         Low       Close   Adj Close  \
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  
         Volume  Daily Returns  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  ,
            Date        Open        High         Low       Close   Adj Close  \
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  
         Volume  Daily Returns  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  ,
            Date        Open        High         Low       Close   Adj Close  \
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  
         Volume  Daily Returns  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  ,
            Date        Open        High         Low       Close   Adj Close  \
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  
         Volume  Daily Returns  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  ,
            Date        Open        High         Low       Close   Adj Close  \
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  
         Volume  Daily Returns  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  ,
            Date        Open        High         Low       Close   Adj Close  \
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  
         Volume  Daily Returns  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  ,
            Date        Open        High         Low       Close   Adj Close  \
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  
         Volume  Daily Returns  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  ,
            Date        Open        High         Low       Close   Adj Close  \
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  
         Volume  Daily Returns  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  ,
            Date        Open        High         Low       Close   Adj Close  \
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  
         Volume  Daily Returns  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  ,
            Date        Open        High         Low       Close   Adj Close  \
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  
         Volume  Daily Returns  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  ,
            Date        Open        High         Low       Close   Adj Close  \
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  
         Volume  Daily Returns  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  ,
            Date        Open        High         Low       Close   Adj Close  \
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  
         Volume  Daily Returns  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  ,
            Date        Open        High         Low       Close   Adj Close  \
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  
         Volume  Daily Returns  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  ,
            Date        Open        High         Low       Close   Adj Close  \
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  
         Volume  Daily Returns  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  ,
            Date        Open        High         Low       Close   Adj Close  \
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  
         Volume  Daily Returns  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  ,
            Date        Open        High         Low       Close   Adj Close  \
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  
         Volume  Daily Returns  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  ,
            Date        Open        High         Low       Close   Adj Close  \
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  
         Volume  Daily Returns  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  ,
            Date        Open        High         Low       Close   Adj Close  \
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  
         Volume  Daily Returns  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  ,
            Date        Open        High         Low       Close   Adj Close  \
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  
         Volume  Daily Returns  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  ,
            Date        Open        High         Low       Close   Adj Close  \
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  
         Volume  Daily Returns  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  ,
            Date        Open        High         Low       Close   Adj Close  \
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  
         Volume  Daily Returns  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  ,
            Date        Open        High         Low       Close   Adj Close  \
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  
         Volume  Daily Returns  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  ,
            Date        Open        High         Low       Close   Adj Close  \
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  
         Volume  Daily Returns  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  ,
            Date        Open        High         Low       Close   Adj Close  \
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  
         Volume  Daily Returns  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  ,
            Date        Open        High         Low       Close   Adj Close  \
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  
         Volume  Daily Returns  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  ,
            Date        Open        High         Low       Close   Adj Close  \
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  
         Volume  Daily Returns  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  ,
            Date        Open        High         Low       Close   Adj Close  \
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  
         Volume  Daily Returns  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  ,
            Date        Open        High         Low       Close   Adj Close  \
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  
         Volume  Daily Returns  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  ,
            Date        Open        High         Low       Close   Adj Close  \
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  
         Volume  Daily Returns  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  ,
            Date        Open        High         Low       Close   Adj Close  \
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  
         Volume  Daily Returns  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  ,
            Date        Open        High         Low       Close   Adj Close  \
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  
         Volume  Daily Returns  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  ,
            Date        Open        High         Low       Close   Adj Close  \
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  
         Volume  Daily Returns  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  ,
            Date        Open        High         Low       Close   Adj Close  \
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  
         Volume  Daily Returns  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  ,
            Date        Open        High         Low       Close   Adj Close  \
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  
         Volume  Daily Returns  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  ,
            Date        Open        High         Low       Close   Adj Close  \
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  
         Volume  Daily Returns  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  ,
            Date        Open        High         Low       Close   Adj Close  \
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  
         Volume  Daily Returns  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  ,
            Date        Open        High         Low       Close   Adj Close  \
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  
         Volume  Daily Returns  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  ,
            Date        Open        High         Low       Close   Adj Close  \
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  
         Volume  Daily Returns  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  ,
            Date        Open        High         Low       Close   Adj Close  \
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  
         Volume  Daily Returns  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  ,
            Date        Open        High         Low       Close   Adj Close  \
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  
         Volume  Daily Returns  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  ,
            Date        Open        High         Low       Close   Adj Close  \
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  
         Volume  Daily Returns  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  ,
            Date        Open        High         Low       Close   Adj Close  \
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  
         Volume  Daily Returns  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  ,
            Date        Open        High         Low       Close   Adj Close  \
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  
         Volume  Daily Returns  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  ,
            Date        Open        High         Low       Close   Adj Close  \
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  
         Volume  Daily Returns  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  ,
            Date        Open        High         Low       Close   Adj Close  \
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  
         Volume  Daily Returns  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  ,
            Date        Open        High         Low       Close   Adj Close  \
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  
         Volume  Daily Returns  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  ,
            Date        Open        High         Low       Close   Adj Close  \
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  
         Volume  Daily Returns  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  ,
            Date        Open        High         Low       Close   Adj Close  \
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  
         Volume  Daily Returns  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  ,
            Date        Open        High         Low       Close   Adj Close  \
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  
         Volume  Daily Returns  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  ,
            Date        Open        High         Low       Close   Adj Close  \
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  
         Volume  Daily Returns  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  ,
            Date        Open        High         Low       Close   Adj Close  \
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  
         Volume  Daily Returns  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  ,
            Date        Open        High         Low       Close   Adj Close  \
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  
         Volume  Daily Returns  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  ,
            Date        Open        High         Low       Close   Adj Close  \
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  
         Volume  Daily Returns  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  ,
            Date        Open        High         Low       Close   Adj Close  \
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  
         Volume  Daily Returns  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  ,
            Date        Open        High         Low       Close   Adj Close  \
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  
         Volume  Daily Returns  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  ,
            Date        Open        High         Low       Close   Adj Close  \
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  
         Volume  Daily Returns  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  ,
            Date        Open        High         Low       Close   Adj Close  \
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  
         Volume  Daily Returns  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  ,
            Date        Open        High         Low       Close   Adj Close  \
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  
         Volume  Daily Returns  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  ,
            Date        Open        High         Low       Close   Adj Close  \
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  
         Volume  Daily Returns  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  ,
            Date        Open        High         Low       Close   Adj Close  \
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  
         Volume  Daily Returns  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  ,
            Date        Open        High         Low       Close   Adj Close  \
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  
         Volume  Daily Returns  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  ,
            Date        Open        High         Low       Close   Adj Close  \
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  
         Volume  Daily Returns  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  ,
            Date        Open        High         Low       Close   Adj Close  \
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  
         Volume  Daily Returns  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  ,
            Date        Open        High         Low       Close   Adj Close  \
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  
         Volume  Daily Returns  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  ,
            Date        Open        High         Low       Close   Adj Close  \
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  
         Volume  Daily Returns  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  ,
            Date        Open        High         Low       Close   Adj Close  \
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  
         Volume  Daily Returns  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  ,
            Date        Open        High         Low       Close   Adj Close  \
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  
         Volume  Daily Returns  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  ,
            Date        Open        High         Low       Close   Adj Close  \
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  
         Volume  Daily Returns  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  ,
            Date        Open        High         Low       Close   Adj Close  \
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  
         Volume  Daily Returns  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  ,
            Date        Open        High         Low       Close   Adj Close  \
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  
         Volume  Daily Returns  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  ,
            Date        Open        High         Low       Close   Adj Close  \
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  
         Volume  Daily Returns  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  ,
            Date        Open        High         Low       Close   Adj Close  \
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  
         Volume  Daily Returns  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  ,
            Date        Open        High         Low       Close   Adj Close  \
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  
         Volume  Daily Returns  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  ,
            Date        Open        High         Low       Close   Adj Close  \
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  
         Volume  Daily Returns  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  ,
            Date        Open        High         Low       Close   Adj Close  \
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  
         Volume  Daily Returns  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  ,
            Date        Open        High         Low       Close   Adj Close  \
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  
         Volume  Daily Returns  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  ,
            Date        Open        High         Low       Close   Adj Close  \
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  
         Volume  Daily Returns  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  ,
            Date        Open        High         Low       Close   Adj Close  \
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  
         Volume  Daily Returns  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  ,
            Date        Open        High         Low       Close   Adj Close  \
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  
         Volume  Daily Returns  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  ,
            Date        Open        High         Low       Close   Adj Close  \
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  
         Volume  Daily Returns  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  ,
            Date        Open        High         Low       Close   Adj Close  \
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  
         Volume  Daily Returns  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  ,
            Date        Open        High         Low       Close   Adj Close  \
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  
         Volume  Daily Returns  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  ,
            Date        Open        High         Low       Close   Adj Close  \
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  
         Volume  Daily Returns  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  ,
            Date        Open        High         Low       Close   Adj Close  \
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  
         Volume  Daily Returns  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  ,
            Date        Open        High         Low       Close   Adj Close  \
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  
         Volume  Daily Returns  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  ,
            Date        Open        High         Low       Close   Adj Close  \
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  
         Volume  Daily Returns  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  ,
            Date        Open        High         Low       Close   Adj Close  \
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  
         Volume  Daily Returns  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  ,
            Date        Open        High         Low       Close   Adj Close  \
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  
         Volume  Daily Returns  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  ,
            Date        Open        High         Low       Close   Adj Close  \
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  
         Volume  Daily Returns  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  ,
            Date        Open        High         Low       Close   Adj Close  \
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  
         Volume  Daily Returns  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  ,
            Date        Open        High         Low       Close   Adj Close  \
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  
         Volume  Daily Returns  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  ,
            Date        Open        High         Low       Close   Adj Close  \
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  
         Volume  Daily Returns  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  ,
            Date        Open        High         Low       Close   Adj Close  \
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  
         Volume  Daily Returns  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  ,
            Date        Open        High         Low       Close   Adj Close  \
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  
         Volume  Daily Returns  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  ,
            Date        Open        High         Low       Close   Adj Close  \
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  
         Volume  Daily Returns  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  ,
            Date        Open        High         Low       Close   Adj Close  \
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  
         Volume  Daily Returns  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  ,
            Date        Open        High         Low       Close   Adj Close  \
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  
         Volume  Daily Returns  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  ,
            Date        Open        High         Low       Close   Adj Close  \
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  
         Volume  Daily Returns  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  ,
            Date        Open        High         Low       Close   Adj Close  \
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  
         Volume  Daily Returns  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  ,
            Date        Open        High         Low       Close   Adj Close  \
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  
         Volume  Daily Returns  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  ,
            Date        Open        High         Low       Close   Adj Close  \
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  
         Volume  Daily Returns  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  ,
            Date        Open        High         Low       Close   Adj Close  \
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  
         Volume  Daily Returns  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  ,
            Date        Open        High         Low       Close   Adj Close  \
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  
         Volume  Daily Returns  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  ,
            Date        Open        High         Low       Close   Adj Close  \
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  
         Volume  Daily Returns  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  ,
            Date        Open        High         Low       Close   Adj Close  \
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  
         Volume  Daily Returns  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  ,
            Date        Open        High         Low       Close   Adj Close  \
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  
         Volume  Daily Returns  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  ,
            Date        Open        High         Low       Close   Adj Close  \
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  
         Volume  Daily Returns  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  ,
            Date        Open        High         Low       Close   Adj Close  \
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  
         Volume  Daily Returns  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  ,
            Date        Open        High         Low       Close   Adj Close  \
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  
         Volume  Daily Returns  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  ,
            Date        Open        High         Low       Close   Adj Close  \
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  
         Volume  Daily Returns  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  ,
            Date        Open        High         Low       Close   Adj Close  \
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  
         Volume  Daily Returns  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  ,
            Date        Open        High         Low       Close   Adj Close  \
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  
         Volume  Daily Returns  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  ,
            Date        Open        High         Low       Close   Adj Close  \
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  
         Volume  Daily Returns  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  ,
            Date        Open        High         Low       Close   Adj Close  \
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  
         Volume  Daily Returns  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  ,
            Date        Open        High         Low       Close   Adj Close  \
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  
         Volume  Daily Returns  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  ,
            Date        Open        High         Low       Close   Adj Close  \
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  
         Volume  Daily Returns  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  ,
            Date        Open        High         Low       Close   Adj Close  \
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  
         Volume  Daily Returns  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  ,
            Date        Open        High         Low       Close   Adj Close  \
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  
         Volume  Daily Returns  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  ,
            Date        Open        High         Low       Close   Adj Close  \
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  
         Volume  Daily Returns  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  ,
            Date        Open        High         Low       Close   Adj Close  \
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  
         Volume  Daily Returns  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  ,
            Date        Open        High         Low       Close   Adj Close  \
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  
         Volume  Daily Returns  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  ,
            Date        Open        High         Low       Close   Adj Close  \
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  
         Volume  Daily Returns  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  ,
            Date        Open        High         Low       Close   Adj Close  \
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  
         Volume  Daily Returns  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  
  986  77766500      -0.017013  ,
            Date        Open        High         Low       Close   Adj Close  \
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  
         Volume  Daily Returns  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  
  986  77766500      -0.017013  
  987  84416600       0.007207  ,
            Date        Open        High         Low       Close   Adj Close  \
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  
          Volume  Daily Returns  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  ,
            Date        Open        High         Low       Close   Adj Close  \
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  
          Volume  Daily Returns  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  ,
            Date        Open        High         Low       Close   Adj Close  \
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  
          Volume  Daily Returns  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  ,
            Date        Open        High         Low       Close   Adj Close  \
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  
          Volume  Daily Returns  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  ,
            Date        Open        High         Low       Close   Adj Close  \
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  
          Volume  Daily Returns  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  ,
            Date        Open        High         Low       Close   Adj Close  \
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  
         Volume  Daily Returns  
  989  67588800       0.008013  
  990  56005300       0.030114  
  991  39204000       0.004474  
  992  49973700      -0.014714  
  993  52545800       0.010871  ,
            Date        Open        High         Low       Close   Adj Close  \
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  
         Volume  Daily Returns  
  990  56005300       0.030114  
  991  39204000       0.004474  
  992  49973700      -0.014714  
  993  52545800       0.010871  
  994  50166400      -0.014447  ,
            Date        Open        High         Low       Close   Adj Close  \
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  
         Volume  Daily Returns  
  991  39204000       0.004474  
  992  49973700      -0.014714  
  993  52545800       0.010871  
  994  50166400      -0.014447  
  995  75199200      -0.010350  ,
            Date        Open        High         Low       Close   Adj Close  \
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  996 2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  
         Volume  Daily Returns  
  992  49973700      -0.014714  
  993  52545800       0.010871  
  994  50166400      -0.014447  
  995  75199200      -0.010350  
  996  73858000       0.022797  ,
            Date        Open        High         Low       Close   Adj Close  \
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  996 2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  997 2021-12-16  398.040009  398.480011  385.209991  386.839996  380.385498   
  
         Volume  Daily Returns  
  993  52545800       0.010871  
  994  50166400      -0.014447  
  995  75199200      -0.010350  
  996  73858000       0.022797  
  997  82591400      -0.025715  ,
            Date        Open        High         Low       Close   Adj Close  \
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  996 2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  997 2021-12-16  398.040009  398.480011  385.209991  386.839996  380.385498   
  998 2021-12-17  383.329987  389.190002  381.769989  384.910004  378.487732   
  
         Volume  Daily Returns  
  994  50166400      -0.014447  
  995  75199200      -0.010350  
  996  73858000       0.022797  
  997  82591400      -0.025715  
  998  80492500      -0.004989  ,
            Date        Open        High         Low       Close   Adj Close  \
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  996 2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  997 2021-12-16  398.040009  398.480011  385.209991  386.839996  380.385498   
  998 2021-12-17  383.329987  389.190002  381.769989  384.910004  378.487732   
  999 2021-12-20  379.570007  381.500000  377.470001  380.690002  374.816254   
  
         Volume  Daily Returns  
  995  75199200      -0.010350  
  996  73858000       0.022797  
  997  82591400      -0.025715  
  998  80492500      -0.004989  
  999  65336800      -0.009700  ,
             Date        Open        High         Low       Close   Adj Close  \
  996  2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  997  2021-12-16  398.040009  398.480011  385.209991  386.839996  380.385498   
  998  2021-12-17  383.329987  389.190002  381.769989  384.910004  378.487732   
  999  2021-12-20  379.570007  381.500000  377.470001  380.690002  374.816254   
  1000 2021-12-21  384.049988  389.529999  380.200012  389.209991  383.204742   
  
          Volume  Daily Returns  
  996   73858000       0.022797  
  997   82591400      -0.025715  
  998   80492500      -0.004989  
  999   65336800      -0.009700  
  1000  48899500       0.022380  ,
             Date        Open        High         Low       Close   Adj Close  \
  997  2021-12-16  398.040009  398.480011  385.209991  386.839996  380.385498   
  998  2021-12-17  383.329987  389.190002  381.769989  384.910004  378.487732   
  999  2021-12-20  379.570007  381.500000  377.470001  380.690002  374.816254   
  1000 2021-12-21  384.049988  389.529999  380.200012  389.209991  383.204742   
  1001 2021-12-22  388.910004  394.160004  388.230011  393.950012  387.871674   
  
          Volume  Daily Returns  
  997   82591400      -0.025715  
  998   80492500      -0.004989  
  999   65336800      -0.009700  
  1000  48899500       0.022380  
  1001  37042200       0.012179  ,
  ...],
 'Estimation Window': [        Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  
       Volume  Daily Returns  
  0  32573300            NaN  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  
       Volume  Daily Returns  
  0  32573300            NaN  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  
       Volume  Daily Returns  
  0  32573300            NaN  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  
       Volume  Daily Returns  
  0  32573300            NaN  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8 2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  
  8  37762700       0.007349  ,
          Date        Open        High         Low       Close   Adj Close  \
  0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3 2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4 2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5 2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6 2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7 2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8 2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9 2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  
       Volume  Daily Returns  
  0  32573300            NaN  
  1  29383600       0.009717  
  2  24776100       0.001749  
  3  26992300       0.010044  
  4  23159100       0.003890  
  5  24782400       0.000062  
  6  34004000      -0.002338  
  7  20473500       0.006844  
  8  37762700       0.007349  
  9  41231800      -0.002857  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  
  21  38037900      -0.008501  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  
        Volume  Daily Returns  
  0   32573300            NaN  
  1   29383600       0.009717  
  2   24776100       0.001749  
  3   26992300       0.010044  
  4   23159100       0.003890  
  5   24782400       0.000062  
  6   34004000      -0.002338  
  7   20473500       0.006844  
  8   37762700       0.007349  
  9   41231800      -0.002857  
  10  33849900       0.010791  
  11  26432200       0.000181  
  12  38937600       0.003136  
  13  26081400       0.010701  
  14  37989700       0.008268  
  15  54287400      -0.006489  
  16  28925000      -0.000356  
  17  32038200       0.015325  
  18  37277800      -0.004855  
  19  44987700      -0.008231  
  20  42449200       0.004149  
  21  38037900      -0.008501  
  22  68478100      -0.019945  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  ,
           Date        Open        High         Low       Close   Adj Close  \
  0  2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  
         Volume  Daily Returns  
  0    32573300            NaN  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  ,
           Date        Open        High         Low       Close   Adj Close  \
  1  2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  
         Volume  Daily Returns  
  1    29383600       0.009717  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  ,
           Date        Open        High         Low       Close   Adj Close  \
  2  2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  
         Volume  Daily Returns  
  2    24776100       0.001749  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  ,
           Date        Open        High         Low       Close   Adj Close  \
  3  2018-01-05  161.070007  162.029999  160.770004  161.919998  155.158768   
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  
         Volume  Daily Returns  
  3    26992300       0.010044  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  ,
           Date        Open        High         Low       Close   Adj Close  \
  4  2018-01-08  161.919998  162.630005  161.860001  162.550003  155.762390   
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  
         Volume  Daily Returns  
  4    23159100       0.003890  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  ,
           Date        Open        High         Low       Close   Adj Close  \
  5  2018-01-09  162.869995  163.039993  162.070007  162.559998  155.771988   
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  
         Volume  Daily Returns  
  5    24782400       0.000062  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  ,
           Date        Open        High         Low       Close   Adj Close  \
  6  2018-01-10  161.839996  162.210007  161.119995  162.179993  155.407852   
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  
         Volume  Daily Returns  
  6    34004000      -0.002338  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  ,
           Date        Open        High         Low       Close   Adj Close  \
  7  2018-01-11  162.460007  163.300003  162.210007  163.289993  156.471512   
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  
         Volume  Daily Returns  
  7    20473500       0.006844  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  ,
           Date        Open        High         Low       Close   Adj Close  \
  8  2018-01-12  163.149994  164.660004  162.940002  164.490005  157.621429   
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  
         Volume  Daily Returns  
  8    37762700       0.007349  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  ,
           Date        Open        High         Low       Close   Adj Close  \
  9  2018-01-16  165.580002  166.419998  163.529999  164.020004  157.171066   
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  
         Volume  Daily Returns  
  9    41231800      -0.002857  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  ,
           Date        Open        High         Low       Close   Adj Close  \
  10 2018-01-17  164.800003  166.039993  164.000000  165.789993  158.867126   
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  
         Volume  Daily Returns  
  10   33849900       0.010791  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  ,
           Date        Open        High         Low       Close   Adj Close  \
  11 2018-01-18  165.529999  166.199997  165.139999  165.820007  158.895874   
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  
         Volume  Daily Returns  
  11   26432200       0.000181  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  ,
           Date        Open        High         Low       Close   Adj Close  \
  12 2018-01-19  166.309998  166.610001  165.539993  166.339996  159.394180   
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  
         Volume  Daily Returns  
  12   38937600       0.003136  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  ,
           Date        Open        High         Low       Close   Adj Close  \
  13 2018-01-22  166.279999  168.119995  166.089996  168.119995  161.099838   
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  
         Volume  Daily Returns  
  13   26081400       0.010701  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  ,
           Date        Open        High         Low       Close   Adj Close  \
  14 2018-01-23  168.639999  169.660004  168.559998  169.509995  162.431808   
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  
         Volume  Daily Returns  
  14   37989700       0.008268  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  ,
           Date        Open        High         Low       Close   Adj Close  \
  15 2018-01-24  169.869995  170.240005  167.440002  168.410004  161.377731   
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  
         Volume  Daily Returns  
  15   54287400      -0.006489  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  ,
           Date        Open        High         Low       Close   Adj Close  \
  16 2018-01-25  169.570007  169.630005  167.809998  168.350006  161.320221   
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  
         Volume  Daily Returns  
  16   28925000      -0.000356  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  ,
           Date        Open        High         Low       Close   Adj Close  \
  17 2018-01-26  169.289993  170.949997  168.960007  170.929993  163.792511   
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  
         Volume  Daily Returns  
  17   32038200       0.015325  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  ,
           Date        Open        High         Low       Close   Adj Close  \
  18 2018-01-29  170.570007  170.910004  169.740005  170.100006  162.997223   
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  
         Volume  Daily Returns  
  18   37277800      -0.004855  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  ,
           Date        Open        High         Low       Close   Adj Close  \
  19 2018-01-30  168.550003  169.419998  167.820007  168.699997  161.655594   
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  
         Volume  Daily Returns  
  19   44987700      -0.008231  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  ,
           Date        Open        High         Low       Close   Adj Close  \
  20 2018-01-31  169.649994  169.990005  168.339996  169.399994  162.326370   
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  
         Volume  Daily Returns  
  20   42449200       0.004149  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  ,
           Date        Open        High         Low       Close   Adj Close  \
  21 2018-02-01  168.100006  169.729996  167.419998  167.960007  160.946503   
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  
         Volume  Daily Returns  
  21   38037900      -0.008501  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  ,
           Date        Open        High         Low       Close   Adj Close  \
  22 2018-02-02  167.300003  167.699997  164.470001  164.610001  157.736404   
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  
         Volume  Daily Returns  
  22   68478100      -0.019945  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  ,
           Date        Open        High         Low       Close   Adj Close  \
  23 2018-02-05  163.070007  165.750000  158.000000  158.119995  151.517349   
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  
         Volume  Daily Returns  
  23  105372200      -0.039427  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  
  52   71395100      -0.021336  ,
           Date        Open        High         Low       Close   Adj Close  \
  24 2018-02-06  155.809998  162.509995  155.100006  162.309998  155.532440   
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  
         Volume  Daily Returns  
  24  118537900       0.026499  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  
  52   71395100      -0.021336  
  53   34075700       0.003291  ,
           Date        Open        High         Low       Close   Adj Close  \
  25 2018-02-07  161.789993  163.550003  160.199997  160.210007  153.520096   
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  
         Volume  Daily Returns  
  25   91028300      -0.012938  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  
  52   71395100      -0.021336  
  53   34075700       0.003291  
  54   43863500      -0.004354  ,
           Date        Open        High         Low       Close   Adj Close  \
  26 2018-02-08  160.619995  160.800003  153.449997  153.449997  147.042419   
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  
         Volume  Daily Returns  
  26   94184800      -0.042194  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  
  52   71395100      -0.021336  
  53   34075700       0.003291  
  54   43863500      -0.004354  
  55   66607300      -0.024683  ,
           Date        Open        High         Low       Close   Adj Close  \
  27 2018-02-09  155.619995  157.240005  150.130005  156.100006  149.581787   
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  
         Volume  Daily Returns  
  27  113836600       0.017270  
  28   63050600       0.017745  
  29   31785600       0.005161  
  30   52107400       0.018724  
  31   51633900       0.018565  
  32   62256300      -0.004466  
  33   36785600       0.002000  
  34   41161800      -0.002843  
  35   37074400      -0.000121  
  36   50096900       0.020448  
  37   39266700       0.013260  
  38   42209900      -0.012383  
  39   42936300      -0.006417  
  40   76809900      -0.016327  
  41   57445100       0.009180  
  42   38540200       0.011085  
  43   29480900       0.004231  
  44   34609400       0.002314  
  45   25828400       0.005505  
  46   38310500       0.019427  
  47   37635000       0.005314  
  48   55638900      -0.013615  
  49   40536400      -0.000175  
  50   28810400      -0.000873  
  51   31176700      -0.002973  
  52   71395100      -0.021336  
  53   34075700       0.003291  
  54   43863500      -0.004354  
  55   66607300      -0.024683  
  56   80110400      -0.026351  ,
           Date        Open        High         Low       Close   Adj Close  \
  28 2018-02-12  157.699997  159.949997  156.460007  158.869995  152.236084   
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  
        Volume  Daily Returns  
  28  63050600       0.017745  
  29  31785600       0.005161  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  ,
           Date        Open        High         Low       Close   Adj Close  \
  29 2018-02-13  157.960007  160.009995  157.720001  159.690002  153.021835   
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  
        Volume  Daily Returns  
  29  31785600       0.005161  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  ,
           Date        Open        High         Low       Close   Adj Close  \
  30 2018-02-14  158.750000  162.929993  158.000000  162.679993  155.886963   
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  
        Volume  Daily Returns  
  30  52107400       0.018724  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  ,
           Date        Open        High         Low       Close   Adj Close  \
  31 2018-02-15  164.139999  165.699997  162.440002  165.699997  158.780930   
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  
        Volume  Daily Returns  
  31  51633900       0.018565  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  ,
           Date        Open        High         Low       Close   Adj Close  \
  32 2018-02-16  165.160004  166.759995  164.679993  164.960007  158.071793   
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  
        Volume  Daily Returns  
  32  62256300      -0.004466  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  ,
           Date        Open        High         Low       Close   Adj Close  \
  33 2018-02-20  164.380005  166.679993  164.309998  165.289993  158.387985   
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  
        Volume  Daily Returns  
  33  36785600       0.002000  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  ,
           Date        Open        High         Low       Close   Adj Close  \
  34 2018-02-21  166.100006  167.720001  164.720001  164.820007  157.937622   
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  
        Volume  Daily Returns  
  34  41161800      -0.002843  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  ,
           Date        Open        High         Low       Close   Adj Close  \
  35 2018-02-22  165.539993  166.419998  164.380005  164.800003  157.918533   
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  
        Volume  Daily Returns  
  35  37074400      -0.000121  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  ,
           Date        Open        High         Low       Close   Adj Close  \
  36 2018-02-23  166.130005  168.169998  165.449997  168.169998  161.147720   
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  
        Volume  Daily Returns  
  36  50096900       0.020448  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  ,
           Date        Open        High         Low       Close   Adj Close  \
  37 2018-02-26  168.960007  170.399994  168.820007  170.399994  163.284607   
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  
        Volume  Daily Returns  
  37  39266700       0.013260  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  ,
           Date        Open        High         Low       Close   Adj Close  \
  38 2018-02-27  170.449997  170.729996  168.210007  168.289993  161.262726   
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  
        Volume  Daily Returns  
  38  42209900      -0.012383  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  ,
           Date        Open        High         Low       Close   Adj Close  \
  39 2018-02-28  169.250000  169.800003  167.100006  167.210007  160.227844   
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  
        Volume  Daily Returns  
  39  42936300      -0.006417  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  ,
           Date        Open        High         Low       Close   Adj Close  \
  40 2018-03-01  167.300003  168.070007  163.000000  164.479996  157.611832   
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  
        Volume  Daily Returns  
  40  76809900      -0.016327  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  ,
           Date        Open        High         Low       Close   Adj Close  \
  41 2018-03-02  162.500000  166.279999  161.960007  165.990005  159.058777   
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  
        Volume  Daily Returns  
  41  57445100       0.009180  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  ,
           Date        Open        High         Low       Close   Adj Close  \
  42 2018-03-05  165.210007  168.259995  164.589996  167.830002  160.821915   
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  
        Volume  Daily Returns  
  42  38540200       0.011085  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  ,
           Date        Open        High         Low       Close   Adj Close  \
  43 2018-03-06  168.649994  169.110001  167.479996  168.539993  161.502319   
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  
        Volume  Daily Returns  
  43  29480900       0.004231  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  ,
           Date        Open        High         Low       Close   Adj Close  \
  44 2018-03-07  167.250000  169.070007  166.960007  168.929993  161.876022   
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  
        Volume  Daily Returns  
  44  34609400       0.002314  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  ,
           Date        Open        High         Low       Close   Adj Close  \
  45 2018-03-08  169.630005  169.979996  168.949997  169.860001  162.767227   
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  
        Volume  Daily Returns  
  45  25828400       0.005505  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  ,
           Date        Open        High         Low       Close   Adj Close  \
  46 2018-03-09  171.070007  173.160004  170.820007  173.160004  165.929321   
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  
        Volume  Daily Returns  
  46  38310500       0.019427  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  ,
           Date        Open        High         Low       Close   Adj Close  \
  47 2018-03-12  173.669998  174.479996  173.279999  174.080002  166.810989   
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  
        Volume  Daily Returns  
  47  37635000       0.005314  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  ,
           Date        Open        High         Low       Close   Adj Close  \
  48 2018-03-13  174.479996  175.210007  171.270004  171.710007  164.539917   
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  
        Volume  Daily Returns  
  48  55638900      -0.013615  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  ,
           Date        Open        High         Low       Close   Adj Close  \
  49 2018-03-14  172.610001  172.740005  170.929993  171.679993  164.511169   
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  
        Volume  Daily Returns  
  49  40536400      -0.000175  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  ,
           Date        Open        High         Low       Close   Adj Close  \
  50 2018-03-15  171.800003  172.529999  170.899994  171.529999  164.367477   
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  
        Volume  Daily Returns  
  50  28810400      -0.000873  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  ,
           Date        Open        High         Low       Close   Adj Close  \
  51 2018-03-16  171.820007  172.199997  170.940002  171.020004  163.878738   
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  
        Volume  Daily Returns  
  51  31176700      -0.002973  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  ,
           Date        Open        High         Low       Close   Adj Close  \
  52 2018-03-19  169.100006  169.220001  165.639999  167.100006  160.382187   
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  
        Volume  Daily Returns  
  52  71395100      -0.021336  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  ,
           Date        Open        High         Low       Close   Adj Close  \
  53 2018-03-20  167.169998  168.039993  166.610001  167.649994  160.910049   
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  
        Volume  Daily Returns  
  53  34075700       0.003291  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  ,
           Date        Open        High         Low       Close   Adj Close  \
  54 2018-03-21  167.210007  168.759995  166.190002  166.919998  160.209442   
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  
        Volume  Daily Returns  
  54  43863500      -0.004354  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  ,
           Date        Open        High         Low       Close   Adj Close  \
  55 2018-03-22  164.610001  165.770004  162.589996  162.800003  156.255035   
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  
        Volume  Daily Returns  
  55  66607300      -0.024683  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  ,
           Date        Open        High         Low       Close   Adj Close  \
  56 2018-03-23  162.610001  163.300003  158.429993  158.509995  152.137573   
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  
        Volume  Daily Returns  
  56  80110400      -0.026351  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  ,
           Date        Open        High         Low       Close   Adj Close  \
  57 2018-03-26  161.720001  164.600006  159.160004  164.399994  157.790756   
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  
        Volume  Daily Returns  
  57  57481500       0.037158  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  ,
           Date        Open        High         Low       Close   Adj Close  \
  58 2018-03-27  165.619995  165.619995  157.679993  159.080002  152.684616   
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  
        Volume  Daily Returns  
  58  78889100      -0.032360  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  ,
           Date        Open        High         Low       Close   Adj Close  \
  59 2018-03-28  158.169998  159.779999  156.039993  157.250000  150.928192   
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  
        Volume  Daily Returns  
  59  89369700      -0.011504  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  ,
           Date        Open        High         Low       Close   Adj Close  \
  60 2018-03-29  158.100006  161.710007  156.630005  160.130005  153.692398   
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  
        Volume  Daily Returns  
  60  68692600       0.018315  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  ,
           Date        Open        High         Low       Close   Adj Close  \
  61 2018-04-02  158.990005  159.740005  153.880005  155.509995  149.258102   
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  
        Volume  Daily Returns  
  61  85549400      -0.028852  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  ,
           Date        Open        High         Low       Close   Adj Close  \
  62 2018-04-03  156.869995  157.919998  154.440002  157.259995  150.937744   
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  
        Volume  Daily Returns  
  62  64090000       0.011253  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  ,
           Date        Open        High         Low       Close   Adj Close  \
  63 2018-04-04  154.220001  160.229996  154.039993  159.740005  153.318039   
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  
        Volume  Daily Returns  
  63  65768700       0.015770  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  ,
           Date        Open        High         Low       Close   Adj Close  \
  64 2018-04-05  161.330002  161.580002  159.479996  160.649994  154.191498   
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  
        Volume  Daily Returns  
  64  43054900       0.005697  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  ,
           Date        Open        High         Low       Close   Adj Close  \
  65 2018-04-06  158.880005  160.460007  155.880005  156.630005  150.333145   
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  
        Volume  Daily Returns  
  65  59870900      -0.025023  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  ,
           Date        Open        High         Low       Close   Adj Close  \
  66 2018-04-09  157.979996  160.880005  157.460007  157.729996  151.388855   
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  
        Volume  Daily Returns  
  66  41810400       0.007022  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  ,
           Date        Open        High         Low       Close   Adj Close  \
  67 2018-04-10  160.210007  161.729996  159.070007  161.210007  154.728973   
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  
        Volume  Daily Returns  
  67  48296800       0.022063  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  ,
           Date        Open        High         Low       Close   Adj Close  \
  68 2018-04-11  160.199997  162.000000  160.100006  160.279999  153.836411   
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  
        Volume  Daily Returns  
  68  41622100      -0.005769  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  ,
           Date        Open        High         Low       Close   Adj Close  \
  69 2018-04-12  161.250000  162.770004  161.160004  162.210007  155.688812   
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98 2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  
        Volume  Daily Returns  
  69  30467900       0.012041  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  
  98  26557800       0.008443  ,
           Date        Open        High         Low       Close   Adj Close  \
  70 2018-04-13  163.020004  163.259995  160.669998  161.369995  154.882538   
  71 2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72 2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73 2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74 2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75 2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76 2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77 2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78 2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79 2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80 2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81 2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82 2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83 2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84 2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85 2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86 2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87 2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88 2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89 2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90 2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91 2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92 2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93 2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94 2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95 2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96 2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97 2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98 2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99 2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  
        Volume  Daily Returns  
  70  44604900      -0.005179  
  71  28180800       0.007622  
  72  35536100       0.021525  
  73  29573900       0.002047  
  74  34705700      -0.009192  
  75  49197100      -0.015827  
  76  33040600      -0.002526  
  77  70256800      -0.021187  
  78  52089300       0.001199  
  79  43005500       0.021053  
  80  51043400       0.000617  
  81  35615300      -0.007095  
  82  36513500       0.011433  
  83  38646800      -0.005898  
  84  60337100      -0.000123  
  85  41543200       0.018974  
  86  32500200       0.008309  
  87  26040200      -0.001022  
  88  29122700       0.010899  
  89  27067600       0.010365  
  90  24688800      -0.000944  
  91  21821700       0.001711  
  92  49361600      -0.011075  
  93  22941200       0.006612  
  94  27480200      -0.003847  
  95  26217900      -0.005168  
  96  22954600       0.005613  
  97  19477700      -0.001306  
  98  26557800       0.008443  
  99  27696500      -0.000295  ,
            Date        Open        High         Low       Close   Adj Close  \
  71  2018-04-16  162.500000  163.190002  161.479996  162.600006  156.063110   
  72  2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73  2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74  2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75  2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  
         Volume  Daily Returns  
  71   28180800       0.007622  
  72   35536100       0.021525  
  73   29573900       0.002047  
  74   34705700      -0.009192  
  75   49197100      -0.015827  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  ,
            Date        Open        High         Low       Close   Adj Close  \
  72  2018-04-17  164.240005  166.460007  163.910004  166.100006  159.422394   
  73  2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74  2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75  2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  
         Volume  Daily Returns  
  72   35536100       0.021525  
  73   29573900       0.002047  
  74   34705700      -0.009192  
  75   49197100      -0.015827  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  ,
            Date        Open        High         Low       Close   Adj Close  \
  73  2018-04-18  166.100006  167.000000  165.309998  166.440002  159.748734   
  74  2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75  2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  
         Volume  Daily Returns  
  73   29573900       0.002047  
  74   34705700      -0.009192  
  75   49197100      -0.015827  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  ,
            Date        Open        High         Low       Close   Adj Close  \
  74  2018-04-19  165.600006  165.990005  164.339996  164.910004  158.280258   
  75  2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  
         Volume  Daily Returns  
  74   34705700      -0.009192  
  75   49197100      -0.015827  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  ,
            Date        Open        High         Low       Close   Adj Close  \
  75  2018-04-20  164.490005  164.610001  161.729996  162.300003  155.775162   
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  
         Volume  Daily Returns  
  75   49197100      -0.015827  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  ,
            Date        Open        High         Low       Close   Adj Close  \
  76  2018-04-23  163.089996  163.729996  161.020004  161.889999  155.381607   
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  
         Volume  Daily Returns  
  76   33040600      -0.002526  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  ,
            Date        Open        High         Low       Close   Adj Close  \
  77  2018-04-24  162.660004  162.910004  157.389999  158.460007  152.089493   
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  
         Volume  Daily Returns  
  77   70256800      -0.021187  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  ,
            Date        Open        High         Low       Close   Adj Close  \
  78  2018-04-25  158.740005  159.309998  156.470001  158.649994  152.271912   
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  
         Volume  Daily Returns  
  78   52089300       0.001199  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  ,
            Date        Open        High         Low       Close   Adj Close  \
  79  2018-04-26  160.699997  162.529999  160.179993  161.990005  155.477631   
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  
         Volume  Daily Returns  
  79   43005500       0.021053  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  ,
            Date        Open        High         Low       Close   Adj Close  \
  80  2018-04-27  164.369995  164.410004  161.169998  162.089996  155.573608   
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  
         Volume  Daily Returns  
  80   51043400       0.000617  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  ,
            Date        Open        High         Low       Close   Adj Close  \
  81  2018-04-30  162.470001  163.479996  160.539993  160.940002  154.469833   
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  
         Volume  Daily Returns  
  81   35615300      -0.007095  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  ,
            Date        Open        High         Low       Close   Adj Close  \
  82  2018-05-01  160.520004  162.800003  160.139999  162.779999  156.235870   
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  
         Volume  Daily Returns  
  82   36513500       0.011433  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  ,
            Date        Open        High         Low       Close   Adj Close  \
  83  2018-05-02  163.059998  163.570007  161.630005  161.820007  155.314438   
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  
         Volume  Daily Returns  
  83   38646800      -0.005898  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  ,
            Date        Open        High         Low       Close   Adj Close  \
  84  2018-05-03  161.000000  162.399994  159.220001  161.800003  155.295273   
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  
         Volume  Daily Returns  
  84   60337100      -0.000123  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  ,
            Date        Open        High         Low       Close   Adj Close  \
  85  2018-05-04  161.100006  165.250000  160.979996  164.869995  158.241852   
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  
         Volume  Daily Returns  
  85   41543200       0.018974  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  ,
            Date        Open        High         Low       Close   Adj Close  \
  86  2018-05-07  165.639999  166.779999  165.509995  166.240005  159.556747   
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  
         Volume  Daily Returns  
  86   32500200       0.008309  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  ,
            Date        Open        High         Low       Close   Adj Close  \
  87  2018-05-08  165.889999  166.429993  164.860001  166.070007  159.393646   
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  
         Volume  Daily Returns  
  87   26040200      -0.001022  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  ,
            Date        Open        High         Low       Close   Adj Close  \
  88  2018-05-09  166.369995  168.000000  165.779999  167.880005  161.130814   
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  
         Volume  Daily Returns  
  88   29122700       0.010899  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  ,
            Date        Open        High         Low       Close   Adj Close  \
  89  2018-05-10  168.419998  169.740005  168.289993  169.619995  162.800888   
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  
         Volume  Daily Returns  
  89   27067600       0.010365  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  ,
            Date        Open        High         Low       Close   Adj Close  \
  90  2018-05-11  169.419998  169.860001  168.720001  169.460007  162.647278   
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  
         Volume  Daily Returns  
  90   24688800      -0.000944  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  ,
            Date        Open        High         Low       Close   Adj Close  \
  91  2018-05-14  169.850006  170.820007  169.470001  169.750000  162.925629   
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  
         Volume  Daily Returns  
  91   21821700       0.001711  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  ,
            Date        Open        High         Low       Close   Adj Close  \
  92  2018-05-15  168.410004  168.500000  166.979996  167.869995  161.121231   
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  
         Volume  Daily Returns  
  92   49361600      -0.011075  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  ,
            Date        Open        High         Low       Close   Adj Close  \
  93  2018-05-16  168.089996  169.369995  168.009995  168.979996  162.186630   
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  
         Volume  Daily Returns  
  93   22941200       0.006612  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  ,
            Date        Open        High         Low       Close   Adj Close  \
  94  2018-05-17  168.389999  169.610001  167.509995  168.330002  161.562744   
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  
         Volume  Daily Returns  
  94   27480200      -0.003847  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  ,
            Date        Open        High         Low       Close   Adj Close  \
  95  2018-05-18  167.679993  168.259995  167.210007  167.460007  160.727707   
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  
         Volume  Daily Returns  
  95   26217900      -0.005168  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  ,
            Date        Open        High         Low       Close   Adj Close  \
  96  2018-05-21  168.759995  169.500000  167.679993  168.399994  161.629868   
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  
         Volume  Daily Returns  
  96   22954600       0.005613  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  ,
            Date        Open        High         Low       Close   Adj Close  \
  97  2018-05-22  169.169998  169.449997  167.880005  168.179993  161.418762   
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  
         Volume  Daily Returns  
  97   19477700      -0.001306  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  ,
            Date        Open        High         Low       Close   Adj Close  \
  98  2018-05-23  166.899994  169.619995  166.880005  169.600006  162.781647   
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  
         Volume  Daily Returns  
  98   26557800       0.008443  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  ,
            Date        Open        High         Low       Close   Adj Close  \
  99  2018-05-24  169.550003  169.850006  167.839996  169.550003  162.733673   
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  
         Volume  Daily Returns  
  99   27696500      -0.000295  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  ,
            Date        Open        High         Low       Close   Adj Close  \
  100 2018-05-25  169.529999  170.330002  169.210007  169.720001  162.896866   
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  
         Volume  Daily Returns  
  100  27460500       0.001003  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  ,
            Date        Open        High         Low       Close   Adj Close  \
  101 2018-05-29  168.949997  169.919998  167.960007  168.970001  162.177002   
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  
         Volume  Daily Returns  
  101  41220500      -0.004419  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  ,
            Date        Open        High         Low       Close   Adj Close  \
  102 2018-05-30  169.580002  170.479996  169.220001  170.179993  163.338364   
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  
         Volume  Daily Returns  
  102  22665800       0.007161  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  ,
            Date        Open        High         Low       Close   Adj Close  \
  103 2018-05-31  170.179993  171.199997  169.630005  170.070007  163.232773   
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  
         Volume  Daily Returns  
  103  35670900      -0.000646  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  ,
            Date        Open        High         Low       Close   Adj Close  \
  104 2018-06-01  170.919998  172.839996  170.869995  172.740005  165.795441   
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  
         Volume  Daily Returns  
  104  45543300       0.015699  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  ,
            Date        Open        High         Low       Close   Adj Close  \
  105 2018-06-04  173.179993  174.339996  173.070007  174.300003  167.292694   
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  
         Volume  Daily Returns  
  105  20459600       0.009031  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  ,
            Date        Open        High         Low       Close   Adj Close  \
  106 2018-06-05  174.710007  175.130005  174.070007  174.839996  167.810974   
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  
         Volume  Daily Returns  
  106  24779300       0.003098  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  ,
            Date        Open        High         Low       Close   Adj Close  \
  107 2018-06-06  175.020004  175.889999  174.139999  175.860001  168.790039   
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  
         Volume  Daily Returns  
  107  25036600       0.005834  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  ,
            Date        Open        High         Low       Close   Adj Close  \
  108 2018-06-07  175.889999  175.929993  173.550003  174.429993  167.417480   
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  
         Volume  Daily Returns  
  108  39600300      -0.008132  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  ,
            Date        Open        High         Low       Close   Adj Close  \
  109 2018-06-08  173.610001  174.880005  173.179993  174.440002  167.427109   
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  
         Volume  Daily Returns  
  109  31780300       0.000058  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  ,
            Date        Open        High         Low       Close   Adj Close  \
  110 2018-06-11  174.309998  175.339996  174.279999  174.910004  167.878220   
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  
         Volume  Daily Returns  
  110  22319700       0.002694  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  ,
            Date        Open        High         Low       Close   Adj Close  \
  111 2018-06-12  175.149994  176.000000  174.960007  175.830002  168.761246   
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  
         Volume  Daily Returns  
  111  22511800       0.005260  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  ,
            Date        Open        High         Low       Close   Adj Close  \
  112 2018-06-13  176.100006  177.139999  175.429993  175.820007  168.751663   
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  
         Volume  Daily Returns  
  112  37858600      -0.000057  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  ,
            Date        Open        High         Low       Close   Adj Close  \
  113 2018-06-14  176.630005  177.889999  176.500000  177.600006  170.460098   
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  
         Volume  Daily Returns  
  113  35916000       0.010124  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  ,
            Date        Open        High         Low       Close   Adj Close  \
  114 2018-06-15  176.929993  177.330002  176.110001  176.979996  169.864960   
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  
         Volume  Daily Returns  
  114  49615700      -0.003491  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  ,
            Date        Open        High         Low       Close   Adj Close  \
  115 2018-06-18  175.490005  176.649994  174.940002  176.500000  169.766907   
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  
         Volume  Daily Returns  
  115  31633200      -0.000577  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  ,
            Date        Open        High         Low       Close   Adj Close  \
  116 2018-06-19  174.270004  176.039993  173.710007  176.000000  169.285950   
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  
         Volume  Daily Returns  
  116  38236000      -0.002833  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  ,
            Date        Open        High         Low       Close   Adj Close  \
  117 2018-06-20  176.809998  177.979996  176.649994  177.250000  170.488281   
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  
         Volume  Daily Returns  
  117  33038000       0.007102  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  ,
            Date        Open        High         Low       Close   Adj Close  \
  118 2018-06-21  177.699997  177.880005  175.369995  175.710007  169.007019   
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  
         Volume  Daily Returns  
  118  43469400      -0.008688  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  ,
            Date        Open        High         Low       Close   Adj Close  \
  119 2018-06-22  176.300003  176.369995  174.690002  175.320007  168.631897   
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  
         Volume  Daily Returns  
  119  30073200      -0.002220  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  ,
            Date        Open        High         Low       Close   Adj Close  \
  120 2018-06-25  173.729996  173.990005  169.809998  171.369995  164.832596   
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  
         Volume  Daily Returns  
  120  77799700      -0.022530  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  ,
            Date        Open        High         Low       Close   Adj Close  \
  121 2018-06-26  172.000000  173.059998  171.369995  172.070007  165.505890   
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  
         Volume  Daily Returns  
  121  39008100       0.004085  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  ,
            Date        Open        High         Low       Close   Adj Close  \
  122 2018-06-27  172.800003  173.580002  169.610001  169.729996  163.255142   
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  
         Volume  Daily Returns  
  122  52843500      -0.013599  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  ,
            Date        Open        High         Low       Close   Adj Close  \
  123 2018-06-28  169.520004  171.770004  169.169998  171.190002  164.659439   
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  
         Volume  Daily Returns  
  123  46407700       0.008602  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  ,
            Date        Open        High         Low       Close   Adj Close  \
  124 2018-06-29  172.009995  172.919998  171.399994  171.649994  165.101868   
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  
         Volume  Daily Returns  
  124  36408500       0.002687  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  ,
            Date        Open        High         Low       Close   Adj Close  \
  125 2018-07-02  170.039993  172.850006  169.669998  172.800003  166.208038   
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  
         Volume  Daily Returns  
  125  31770000       0.006700  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  ,
            Date        Open        High         Low       Close   Adj Close  \
  126 2018-07-03  173.449997  173.449997  170.630005  170.800003  164.284332   
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  
         Volume  Daily Returns  
  126  25512700      -0.011574  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  ,
            Date        Open        High         Low       Close   Adj Close  \
  127 2018-07-05  171.910004  173.059998  171.029999  172.919998  166.323425   
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  
         Volume  Daily Returns  
  127  31626200       0.012412  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  ,
            Date        Open        High         Low       Close   Adj Close  \
  128 2018-07-06  173.320007  175.740005  173.000000  175.610001  168.910873   
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  
         Volume  Daily Returns  
  128  37005600       0.015557  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  ,
            Date        Open        High         Low       Close   Adj Close  \
  129 2018-07-09  176.520004  177.229996  175.820007  177.190002  170.430573   
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  
         Volume  Daily Returns  
  129  27362100       0.008997  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  ,
            Date        Open        High         Low       Close   Adj Close  \
  130 2018-07-10  177.520004  177.720001  176.710007  177.320007  170.555618   
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  
         Volume  Daily Returns  
  130  23902500       0.000734  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  ,
            Date        Open        High         Low       Close   Adj Close  \
  131 2018-07-11  175.929993  177.070007  175.800003  176.419998  169.689957   
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  
         Volume  Daily Returns  
  131  30280600      -0.005076  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  ,
            Date        Open        High         Low       Close   Adj Close  \
  132 2018-07-12  177.199997  179.460007  177.080002  179.460007  172.613953   
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  
         Volume  Daily Returns  
  132  27930100       0.017231  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  ,
            Date        Open        High         Low       Close   Adj Close  \
  133 2018-07-13  179.449997  179.899994  178.949997  179.610001  172.758240   
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  
         Volume  Daily Returns  
  133  28049800       0.000836  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  ,
            Date        Open        High         Low       Close   Adj Close  \
  134 2018-07-16  179.649994  179.949997  178.880005  179.179993  172.344635   
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  
         Volume  Daily Returns  
  134  21405300      -0.002394  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  ,
            Date        Open        High         Low       Close   Adj Close  \
  135 2018-07-17  177.279999  180.649994  177.279999  180.270004  173.393082   
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  
         Volume  Daily Returns  
  135  31034100       0.006083  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  ,
            Date        Open        High         Low       Close   Adj Close  \
  136 2018-07-18  180.289993  180.440002  179.380005  179.929993  173.066010   
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  
         Volume  Daily Returns  
  136  23220800      -0.001886  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  ,
            Date        Open        High         Low       Close   Adj Close  \
  137 2018-07-19  179.279999  179.880005  178.820007  179.029999  172.200378   
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  
         Volume  Daily Returns  
  137  31094100      -0.005002  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  ,
            Date        Open        High         Low       Close   Adj Close  \
  138 2018-07-20  179.570007  180.169998  178.789993  178.990005  172.161911   
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  
         Volume  Daily Returns  
  138  35897300      -0.000223  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  ,
            Date        Open        High         Low       Close   Adj Close  \
  139 2018-07-23  178.460007  179.639999  177.740005  179.559998  172.710175   
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  
         Volume  Daily Returns  
  139  22184700       0.003185  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  ,
            Date        Open        High         Low       Close   Adj Close  \
  140 2018-07-24  181.410004  182.050003  179.559998  180.300003  173.421921   
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  
         Volume  Daily Returns  
  140  36900300       0.004121  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  ,
            Date        Open        High         Low       Close   Adj Close  \
  141 2018-07-25  180.380005  182.929993  180.289993  182.820007  175.845825   
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  
         Volume  Daily Returns  
  141  35026600       0.013977  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  ,
            Date        Open        High         Low       Close   Adj Close  \
  142 2018-07-26  180.339996  180.919998  179.809998  180.050003  173.181458   
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  
         Volume  Daily Returns  
  142  40873500      -0.015152  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  ,
            Date        Open        High         Low       Close   Adj Close  \
  143 2018-07-27  181.190002  181.309998  176.600006  177.619995  170.844147   
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  
         Volume  Daily Returns  
  143  59456100      -0.013496  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  ,
            Date        Open        High         Low       Close   Adj Close  \
  144 2018-07-30  177.630005  177.729996  174.270004  175.110001  168.429901   
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  
         Volume  Daily Returns  
  144  60193000      -0.014131  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  ,
            Date        Open        High         Low       Close   Adj Close  \
  145 2018-07-31  175.800003  177.130005  174.820007  176.449997  169.718781   
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  
         Volume  Daily Returns  
  145  47285100       0.007652  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  ,
            Date        Open        High         Low       Close   Adj Close  \
  146 2018-08-01  176.860001  177.649994  176.100006  177.119995  170.363235   
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  
         Volume  Daily Returns  
  146  37101900       0.003797  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  ,
            Date        Open        High         Low       Close   Adj Close  \
  147 2018-08-02  175.869995  179.740005  175.789993  179.529999  172.681305   
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  
         Volume  Daily Returns  
  147  47178200       0.013607  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  ,
            Date        Open        High         Low       Close   Adj Close  \
  148 2018-08-03  179.869995  180.089996  179.080002  180.080002  173.210266   
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  
         Volume  Daily Returns  
  148  28934400       0.003063  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  ,
            Date        Open        High         Low       Close   Adj Close  \
  149 2018-08-06  179.960007  181.190002  179.740005  181.139999  174.229858   
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  
         Volume  Daily Returns  
  149  24808800       0.005886  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  ,
            Date        Open        High         Low       Close   Adj Close  \
  150 2018-08-07  181.649994  182.139999  181.259995  181.800003  174.864700   
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  
         Volume  Daily Returns  
  150  29895700       0.003644  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  ,
            Date        Open        High         Low       Close   Adj Close  \
  151 2018-08-08  181.550003  182.350006  181.059998  182.020004  175.076309   
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  
         Volume  Daily Returns  
  151  22680700       0.001210  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  ,
            Date        Open        High         Low       Close   Adj Close  \
  152 2018-08-09  181.910004  182.630005  181.639999  181.910004  174.970535   
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  
         Volume  Daily Returns  
  152  18852900      -0.000604  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  ,
            Date        Open        High         Low       Close   Adj Close  \
  153 2018-08-10  180.679993  181.220001  179.839996  180.520004  173.633499   
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  
         Volume  Daily Returns  
  153  33818500      -0.007641  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  ,
            Date        Open        High         Low       Close   Adj Close  \
  154 2018-08-13  180.850006  182.009995  180.240005  180.320007  173.441177   
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  
         Volume  Daily Returns  
  154  26089200      -0.001108  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  ,
            Date        Open        High         Low       Close   Adj Close  \
  155 2018-08-14  181.009995  181.660004  180.039993  181.449997  174.528046   
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  
         Volume  Daily Returns  
  155  20913000       0.006266  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  ,
            Date        Open        High         Low       Close   Adj Close  \
  156 2018-08-15  180.009995  180.580002  178.119995  179.229996  172.392761   
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  
         Volume  Daily Returns  
  156  58528000      -0.012235  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  ,
            Date        Open        High         Low       Close   Adj Close  \
  157 2018-08-16  180.610001  180.990005  179.470001  179.820007  172.960205   
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  
         Volume  Daily Returns  
  157  27711800       0.003292  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  ,
            Date        Open        High         Low       Close   Adj Close  \
  158 2018-08-17  179.350006  180.309998  178.270004  179.860001  172.998718   
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  
         Volume  Daily Returns  
  158  36092600       0.000223  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  ,
            Date        Open        High         Low       Close   Adj Close  \
  159 2018-08-20  180.259995  180.330002  179.000000  179.699997  172.844803   
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  
         Volume  Daily Returns  
  159  24939000      -0.000890  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  ,
            Date        Open        High         Low       Close   Adj Close  \
  160 2018-08-21  180.240005  181.440002  180.130005  180.360001  173.479645   
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  
         Volume  Daily Returns  
  160  26258700       0.003673  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  ,
            Date        Open        High         Low       Close   Adj Close  \
  161 2018-08-22  179.979996  181.270004  179.750000  181.059998  174.152924   
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  
         Volume  Daily Returns  
  161  18042400       0.003881  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  ,
            Date        Open        High         Low       Close   Adj Close  \
  162 2018-08-23  180.740005  182.050003  180.500000  180.800003  173.902832   
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  
         Volume  Daily Returns  
  162  25776200      -0.001436  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  ,
            Date        Open        High         Low       Close   Adj Close  \
  163 2018-08-24  181.399994  182.630005  181.360001  182.479996  175.518753   
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  
         Volume  Daily Returns  
  163  23136100       0.009292  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  ,
            Date        Open        High         Low       Close   Adj Close  \
  164 2018-08-27  183.399994  184.339996  183.110001  184.339996  177.307831   
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  
         Volume  Daily Returns  
  164  29343600       0.010193  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  
  193  66864500      -0.006106  ,
            Date        Open        High         Low       Close   Adj Close  \
  165 2018-08-28  184.830002  185.020004  184.220001  184.610001  177.567490   
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  
         Volume  Daily Returns  
  165  20277000       0.001464  
  166  29175600       0.011538  
  167  29315500      -0.001767  
  168  28653200       0.001287  
  169  29063500      -0.004286  
  170  42623300      -0.012914  
  171  46091400      -0.008940  
  172  46629500      -0.003850  
  173  26132000       0.003368  
  174  30116500       0.007704  
  175  36204000      -0.002949  
  176  31133200       0.010680  
  177  31224100      -0.002926  
  178  33071200      -0.014403  
  179  31877300       0.008272  
  180  31843400      -0.000766  
  181  33295800       0.011057  
  182  38605400      -0.005468  
  183  34945600       0.002781  
  184  25277500       0.001359  
  185  36210600       0.000706  
  186  33113300       0.008466  
  187  28076800      -0.000215  
  188  27371300       0.002045  
  189  25618600      -0.002256  
  190  29128700       0.001077  
  191  80557300      -0.019199  
  192  83325600      -0.012227  
  193  66864500      -0.006106  
  194  49097900       0.003239  ,
            Date        Open        High         Low       Close   Adj Close  \
  166 2018-08-29  184.929993  186.839996  184.860001  186.740005  179.616257   
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  
          Volume  Daily Returns  
  166   29175600       0.011538  
  167   29315500      -0.001767  
  168   28653200       0.001287  
  169   29063500      -0.004286  
  170   42623300      -0.012914  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  ,
            Date        Open        High         Low       Close   Adj Close  \
  167 2018-08-30  186.380005  187.520004  185.789993  186.410004  179.298813   
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  
          Volume  Daily Returns  
  167   29315500      -0.001767  
  168   28653200       0.001287  
  169   29063500      -0.004286  
  170   42623300      -0.012914  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  ,
            Date        Open        High         Low       Close   Adj Close  \
  168 2018-08-31  186.179993  187.179993  185.979996  186.649994  179.529648   
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  
          Volume  Daily Returns  
  168   28653200       0.001287  
  169   29063500      -0.004286  
  170   42623300      -0.012914  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  ,
            Date        Open        High         Low       Close   Adj Close  \
  169 2018-09-04  186.080002  186.399994  184.850006  185.850006  178.760193   
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  
          Volume  Daily Returns  
  169   29063500      -0.004286  
  170   42623300      -0.012914  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  ,
            Date        Open        High         Low       Close   Adj Close  \
  170 2018-09-05  185.520004  185.550003  182.820007  183.449997  176.451736   
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  
          Volume  Daily Returns  
  170   42623300      -0.012914  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  ,
            Date        Open        High         Low       Close   Adj Close  \
  171 2018-09-06  183.529999  183.750000  180.580002  181.809998  174.874313   
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  
          Volume  Daily Returns  
  171   46091400      -0.008940  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  ,
            Date        Open        High         Low       Close   Adj Close  \
  172 2018-09-07  180.500000  182.669998  180.440002  181.110001  174.201019   
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  
          Volume  Daily Returns  
  172   46629500      -0.003850  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  ,
            Date        Open        High         Low       Close   Adj Close  \
  173 2018-09-10  182.149994  182.250000  180.729996  181.720001  174.787735   
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  
          Volume  Daily Returns  
  173   26132000       0.003368  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  ,
            Date        Open        High         Low       Close   Adj Close  \
  174 2018-09-11  180.990005  183.419998  180.520004  183.119995  176.134338   
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  
          Volume  Daily Returns  
  174   30116500       0.007704  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  ,
            Date        Open        High         Low       Close   Adj Close  \
  175 2018-09-12  182.850006  182.979996  181.009995  182.580002  175.614929   
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  
          Volume  Daily Returns  
  175   36204000      -0.002949  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  ,
            Date        Open        High         Low       Close   Adj Close  \
  176 2018-09-13  183.720001  184.880005  183.639999  184.529999  177.490540   
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  
          Volume  Daily Returns  
  176   31133200       0.010680  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  ,
            Date        Open        High         Low       Close   Adj Close  \
  177 2018-09-14  184.660004  184.949997  183.259995  183.990005  176.971130   
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  
          Volume  Daily Returns  
  177   31224100      -0.002926  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  ,
            Date        Open        High         Low       Close   Adj Close  \
  178 2018-09-17  183.679993  183.809998  181.169998  181.339996  174.422226   
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  
          Volume  Daily Returns  
  178   33071200      -0.014403  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  ,
            Date        Open        High         Low       Close   Adj Close  \
  179 2018-09-18  181.490005  183.729996  181.399994  182.839996  175.865021   
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  
          Volume  Daily Returns  
  179   31877300       0.008272  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  ,
            Date        Open        High         Low       Close   Adj Close  \
  180 2018-09-19  182.869995  183.300003  181.509995  182.699997  175.730362   
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  
          Volume  Daily Returns  
  180   31843400      -0.000766  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  ,
            Date        Open        High         Low       Close   Adj Close  \
  181 2018-09-20  183.960007  184.970001  183.520004  184.720001  177.673325   
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  
          Volume  Daily Returns  
  181   33295800       0.011057  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  ,
            Date        Open        High         Low       Close   Adj Close  \
  182 2018-09-21  185.220001  185.479996  183.479996  183.710007  176.701843   
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  
          Volume  Daily Returns  
  182   38605400      -0.005468  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  ,
            Date        Open        High         Low       Close   Adj Close  \
  183 2018-09-24  182.050003  183.960007  181.300003  183.889999  177.193253   
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  
          Volume  Daily Returns  
  183   34945600       0.002781  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  ,
            Date        Open        High         Low       Close   Adj Close  \
  184 2018-09-25  183.809998  184.279999  183.179993  184.139999  177.434143   
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  
          Volume  Daily Returns  
  184   25277500       0.001359  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  ,
            Date        Open        High         Low       Close   Adj Close  \
  185 2018-09-26  184.300003  185.990005  183.910004  184.270004  177.559448   
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  
          Volume  Daily Returns  
  185   36210600       0.000706  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  ,
            Date        Open        High         Low       Close   Adj Close  \
  186 2018-09-27  185.020004  186.490005  184.919998  185.830002  179.062622   
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  
          Volume  Daily Returns  
  186   33113300       0.008466  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  ,
            Date        Open        High         Low       Close   Adj Close  \
  187 2018-09-28  185.309998  186.279999  184.970001  185.789993  179.024063   
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  
          Volume  Daily Returns  
  187   28076800      -0.000215  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  ,
            Date        Open        High         Low       Close   Adj Close  \
  188 2018-10-01  186.869995  187.529999  185.699997  186.169998  179.390244   
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  
          Volume  Daily Returns  
  188   27371300       0.002045  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  ,
            Date        Open        High         Low       Close   Adj Close  \
  189 2018-10-02  186.009995  187.179993  185.320007  185.750000  178.985504   
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  
          Volume  Daily Returns  
  189   25618600      -0.002256  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  ,
            Date        Open        High         Low       Close   Adj Close  \
  190 2018-10-03  186.529999  186.970001  185.660004  185.949997  179.178238   
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  
          Volume  Daily Returns  
  190   29128700       0.001077  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  ,
            Date        Open        High         Low       Close   Adj Close  \
  191 2018-10-04  185.199997  185.320007  181.059998  182.380005  175.738281   
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  
          Volume  Daily Returns  
  191   80557300      -0.019199  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  ,
            Date        Open        High         Low       Close   Adj Close  \
  192 2018-10-05  182.360001  182.970001  178.429993  180.149994  173.589462   
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  
          Volume  Daily Returns  
  192   83325600      -0.012227  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  ,
            Date        Open        High         Low       Close   Adj Close  \
  193 2018-10-08  179.520004  180.639999  176.929993  179.050003  172.529495   
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  
          Volume  Daily Returns  
  193   66864500      -0.006106  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  ,
            Date        Open        High         Low       Close   Adj Close  \
  194 2018-10-09  179.179993  181.020004  178.750000  179.630005  173.088394   
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  
          Volume  Daily Returns  
  194   49097900       0.003239  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  ,
            Date        Open        High         Low       Close   Adj Close  \
  195 2018-10-10  178.509995  178.619995  171.500000  171.729996  165.476044   
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  
          Volume  Daily Returns  
  195  114471100      -0.043980  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  ,
            Date        Open        High         Low       Close   Adj Close  \
  196 2018-10-11  171.020004  173.399994  167.809998  169.600006  163.423660   
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  
          Volume  Daily Returns  
  196  143084500      -0.012403  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  ,
            Date        Open        High         Low       Close   Adj Close  \
  197 2018-10-12  174.169998  174.860001  170.929993  174.320007  167.971771   
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  
          Volume  Daily Returns  
  197  102078400       0.027830  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  ,
            Date        Open        High         Low       Close   Adj Close  \
  198 2018-10-15  173.710007  174.039993  171.559998  172.210007  165.938644   
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  
          Volume  Daily Returns  
  198   64885300      -0.012104  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  ,
            Date        Open        High         Low       Close   Adj Close  \
  199 2018-10-16  174.020004  177.649994  173.699997  177.220001  170.766144   
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  
          Volume  Daily Returns  
  199   71979700       0.029092  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  ,
            Date        Open        High         Low       Close   Adj Close  \
  200 2018-10-17  178.080002  178.259995  175.470001  177.289993  170.833603   
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  
          Volume  Daily Returns  
  200   66987600       0.000395  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  ,
            Date        Open        High         Low       Close   Adj Close  \
  201 2018-10-18  176.619995  176.679993  172.440002  173.179993  166.873291   
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  
          Volume  Daily Returns  
  201   82486200      -0.023182  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  ,
            Date        Open        High         Low       Close   Adj Close  \
  202 2018-10-19  174.580002  176.070007  172.389999  173.020004  166.719101   
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  
          Volume  Daily Returns  
  202   82923700      -0.000924  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  ,
            Date        Open        High         Low       Close   Adj Close  \
  203 2018-10-22  174.059998  175.250000  172.589996  173.910004  167.576706   
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  
          Volume  Daily Returns  
  203   52909300       0.005144  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  ,
            Date        Open        High         Low       Close   Adj Close  \
  204 2018-10-23  170.639999  174.130005  168.820007  173.270004  166.960037   
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  
          Volume  Daily Returns  
  204   77567000      -0.003680  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  ,
            Date        Open        High         Low       Close   Adj Close  \
  205 2018-10-24  173.070007  173.360001  165.039993  165.339996  159.318787   
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  
          Volume  Daily Returns  
  205  102997400      -0.045767  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  ,
            Date        Open        High         Low       Close   Adj Close  \
  206 2018-10-25  167.910004  172.080002  167.160004  171.059998  164.830505   
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  
          Volume  Daily Returns  
  206   83481100       0.034596  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  ,
            Date        Open        High         Low       Close   Adj Close  \
  207 2018-10-26  165.199997  169.960007  164.229996  166.660004  160.590729   
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  
          Volume  Daily Returns  
  207  130970900      -0.025722  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  ,
            Date        Open        High         Low       Close   Adj Close  \
  208 2018-10-29  169.210007  169.860001  160.089996  163.229996  157.285629   
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  
          Volume  Daily Returns  
  208  111871900      -0.020581  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  ,
            Date        Open        High         Low       Close   Adj Close  \
  209 2018-10-30  162.750000  166.039993  162.009995  165.919998  159.877701   
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  
          Volume  Daily Returns  
  209   92584000       0.016480  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  ,
            Date        Open        High         Low       Close   Adj Close  \
  210 2018-10-31  168.619995  171.250000  168.539993  169.820007  163.635666   
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  
          Volume  Daily Returns  
  210   73828600       0.023505  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  ,
            Date        Open        High         Low       Close   Adj Close  \
  211 2018-11-01  170.070007  172.240005  168.779999  172.059998  165.794052   
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  
          Volume  Daily Returns  
  211   52706800       0.013190  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  ,
            Date        Open        High         Low       Close   Adj Close  \
  212 2018-11-02  171.529999  172.550003  168.220001  169.380005  163.211670   
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  
          Volume  Daily Returns  
  212   75966800      -0.015576  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  ,
            Date        Open        High         Low       Close   Adj Close  \
  213 2018-11-05  169.600006  169.660004  167.080002  168.960007  162.806992   
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  
          Volume  Daily Returns  
  213   39573500      -0.002479  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  ,
            Date        Open        High         Low       Close   Adj Close  \
  214 2018-11-06  168.970001  171.190002  168.720001  170.240005  164.040344   
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  
          Volume  Daily Returns  
  214   34410400       0.007576  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  ,
            Date        Open        High         Low       Close   Adj Close  \
  215 2018-11-07  172.279999  175.580002  171.869995  175.580002  169.185898   
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  
          Volume  Daily Returns  
  215   51169600       0.031368  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  ,
            Date        Open        High         Low       Close   Adj Close  \
  216 2018-11-08  174.759995  175.300003  173.630005  174.460007  168.106659   
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  
          Volume  Daily Returns  
  216   40296500      -0.006379  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  ,
            Date        Open        High         Low       Close   Adj Close  \
  217 2018-11-09  172.830002  173.250000  170.160004  171.520004  165.273712   
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  
          Volume  Daily Returns  
  217   50602700      -0.016852  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  ,
            Date        Open        High         Low       Close   Adj Close  \
  218 2018-11-12  170.320007  170.639999  166.179993  166.330002  160.272736   
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  
          Volume  Daily Returns  
  218   62578400      -0.030259  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  ,
            Date        Open        High         Low       Close   Adj Close  \
  219 2018-11-13  167.110001  169.479996  166.000000  166.470001  160.407654   
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  
          Volume  Daily Returns  
  219   64128100       0.000842  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  ,
            Date        Open        High         Low       Close   Adj Close  \
  220 2018-11-14  168.119995  168.699997  164.250000  165.199997  159.183899   
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  
          Volume  Daily Returns  
  220   75270700      -0.007629  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  ,
            Date        Open        High         Low       Close   Adj Close  \
  221 2018-11-15  164.899994  168.539993  163.460007  168.089996  161.968658   
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  
          Volume  Daily Returns  
  221   73254300       0.017494  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  ,
            Date        Open        High         Low       Close   Adj Close  \
  222 2018-11-16  166.449997  168.309998  165.779999  167.500000  161.400085   
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  
          Volume  Daily Returns  
  222   65390700      -0.003510  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  ,
            Date        Open        High         Low       Close   Adj Close  \
  223 2018-11-19  166.699997  166.899994  161.539993  162.059998  156.158279   
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  
          Volume  Daily Returns  
  223   67280500      -0.032477  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  ,
            Date        Open        High         Low       Close   Adj Close  \
  224 2018-11-20  158.369995  161.380005  157.130005  159.160004  153.363846   
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  
          Volume  Daily Returns  
  224  102652800      -0.017895  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  ,
            Date        Open        High         Low       Close   Adj Close  \
  225 2018-11-21  161.350006  161.970001  159.229996  160.369995  154.529800   
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  
          Volume  Daily Returns  
  225   42965800       0.007603  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  ,
            Date        Open        High         Low       Close   Adj Close  \
  226 2018-11-23  159.089996  160.839996  159.089996  159.210007  153.412033   
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  
          Volume  Daily Returns  
  226   23503700      -0.007233  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  ,
            Date        Open        High         Low       Close   Adj Close  \
  227 2018-11-26  161.440002  162.970001  160.759995  162.889999  156.958038   
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  
          Volume  Daily Returns  
  227   42012600       0.023114  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  ,
            Date        Open        High         Low       Close   Adj Close  \
  228 2018-11-27  162.000000  163.850006  161.179993  163.440002  157.487991   
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  
          Volume  Daily Returns  
  228   36608100       0.003376  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  ,
            Date        Open        High         Low       Close   Adj Close  \
  229 2018-11-28  164.619995  168.699997  163.470001  168.699997  162.556427   
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  
          Volume  Daily Returns  
  229   70141000       0.032183  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  ,
            Date        Open        High         Low       Close   Adj Close  \
  230 2018-11-29  167.990005  169.259995  166.820007  168.149994  162.026474   
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  
          Volume  Daily Returns  
  230   44885700      -0.003260  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  ,
            Date        Open        High         Low       Close   Adj Close  \
  231 2018-11-30  168.380005  169.470001  167.539993  169.369995  163.202042   
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  
          Volume  Daily Returns  
  231   36722800       0.007255  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  ,
            Date        Open        High         Low       Close   Adj Close  \
  232 2018-12-03  173.110001  173.309998  169.509995  172.330002  166.054214   
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  
          Volume  Daily Returns  
  232   50771700       0.017476  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  ,
            Date        Open        High         Low       Close   Adj Close  \
  233 2018-12-04  171.429993  171.910004  165.520004  165.720001  159.684937   
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  
          Volume  Daily Returns  
  233   70594700      -0.038357  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  ,
            Date        Open        High         Low       Close   Adj Close  \
  234 2018-12-06  162.380005  166.910004  161.770004  166.889999  160.812347   
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  
          Volume  Daily Returns  
  234   71715500       0.007060  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  ,
            Date        Open        High         Low       Close   Adj Close  \
  235 2018-12-07  166.160004  167.119995  160.860001  161.380005  155.503006   
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  
          Volume  Daily Returns  
  235   80432200      -0.033016  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  ,
            Date        Open        High         Low       Close   Adj Close  \
  236 2018-12-10  161.080002  163.779999  159.410004  163.070007  157.131470   
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  
          Volume  Daily Returns  
  236   73960800       0.010472  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  ,
            Date        Open        High         Low       Close   Adj Close  \
  237 2018-12-11  165.729996  165.770004  162.229996  163.610001  157.651810   
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  
          Volume  Daily Returns  
  237   59058300       0.003311  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  ,
            Date        Open        High         Low       Close   Adj Close  \
  238 2018-12-12  166.000000  167.600006  164.960007  165.050003  159.039352   
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  
          Volume  Daily Returns  
  238   53780000       0.008801  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  ,
            Date        Open        High         Low       Close   Adj Close  \
  239 2018-12-13  166.130005  166.820007  164.029999  165.100006  159.087524   
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  
          Volume  Daily Returns  
  239   46378500       0.000303  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  ,
            Date        Open        High         Low       Close   Adj Close  \
  240 2018-12-14  163.210007  163.809998  160.699997  161.080002  155.213928   
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  
          Volume  Daily Returns  
  240   56547400      -0.024349  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  ,
            Date        Open        High         Low       Close   Adj Close  \
  241 2018-12-17  160.389999  161.669998  156.169998  157.429993  151.696823   
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  
          Volume  Daily Returns  
  241   74834100      -0.022660  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  
  270   41346500       0.025438  ,
            Date        Open        High         Low       Close   Adj Close  \
  242 2018-12-18  158.649994  159.949997  157.039993  158.419998  152.650772   
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  
          Volume  Daily Returns  
  242   63642100       0.006289  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  
  270   41346500       0.025438  
  271   37258400       0.014969  ,
            Date        Open        High         Low       Close   Adj Close  \
  243 2018-12-19  158.179993  160.720001  153.339996  154.529999  148.902496   
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  
          Volume  Daily Returns  
  243   81856500      -0.024555  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  
  270   41346500       0.025438  
  271   37258400       0.014969  
  272   32143700      -0.004222  ,
            Date        Open        High         Low       Close   Adj Close  \
  244 2018-12-20  154.149994  155.869995  150.389999  152.289993  146.744019   
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  
          Volume  Daily Returns  
  244   99002100      -0.014496  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  
  270   41346500       0.025438  
  271   37258400       0.014969  
  272   32143700      -0.004222  
  273   26718800       0.012422  ,
            Date        Open        High         Low       Close   Adj Close  \
  245 2018-12-21  153.050003  154.089996  146.720001  147.570007  142.195969   
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  
          Volume  Daily Returns  
  245  141129400      -0.030993  
  246   56163300      -0.024798  
  247   98982100       0.062439  
  248   85824300       0.003870  
  249   77856600      -0.000523  
  250   53015300       0.008433  
  251   58576700       0.004019  
  252   74820200      -0.032670  
  253   74709300       0.042785  
  254   52059300       0.011905  
  255   49388700       0.009046  
  256   46491700       0.008149  
  257   38943400       0.002860  
  258   30176600      -0.003658  
  259   30710200      -0.008837  
  260   40874200       0.019527  
  261   33812200      -0.000184  
  262   39329000       0.007884  
  263   57183200       0.009900  
  264   56711700      -0.020030  
  265   38106100       0.001297  
  266   32417800       0.006476  
  267   36515900       0.011948  
  268   33491200      -0.012352  
  269   30784200      -0.009441  
  270   41346500       0.025438  
  271   37258400       0.014969  
  272   32143700      -0.004222  
  273   26718800       0.012422  
  274   28156400       0.008848  ,
            Date        Open        High         Low       Close   Adj Close  \
  246 2018-12-24  146.080002  147.979996  143.460007  143.500000  138.669754   
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  
         Volume  Daily Returns  
  246  56163300      -0.024798  
  247  98982100       0.062439  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  ,
            Date        Open        High         Low       Close   Adj Close  \
  247 2018-12-26  145.080002  152.539993  144.089996  152.460007  147.328156   
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  
         Volume  Daily Returns  
  247  98982100       0.062439  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  ,
            Date        Open        High         Low       Close   Adj Close  \
  248 2018-12-27  150.369995  153.179993  147.080002  153.050003  147.898300   
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  
         Volume  Daily Returns  
  248  85824300       0.003870  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  ,
            Date        Open        High         Low       Close   Adj Close  \
  249 2018-12-28  154.149994  155.589996  151.720001  152.970001  147.820969   
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  
         Volume  Daily Returns  
  249  77856600      -0.000523  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  ,
            Date        Open        High         Low       Close   Adj Close  \
  250 2018-12-31  154.470001  154.979996  152.710007  154.259995  149.067566   
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  
         Volume  Daily Returns  
  250  53015300       0.008433  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  ,
            Date        Open        High         Low       Close   Adj Close  \
  251 2019-01-02  150.990005  155.750000  150.880005  154.880005  149.666687   
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  
         Volume  Daily Returns  
  251  58576700       0.004019  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  ,
            Date        Open        High         Low       Close   Adj Close  \
  252 2019-01-03  152.600006  153.259995  149.490005  149.820007  144.777008   
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  
         Volume  Daily Returns  
  252  74820200      -0.032670  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  ,
            Date        Open        High         Low       Close   Adj Close  \
  253 2019-01-04  152.339996  157.000000  151.740005  156.229996  150.971252   
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  
         Volume  Daily Returns  
  253  74709300       0.042785  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  ,
            Date        Open        High         Low       Close   Adj Close  \
  254 2019-01-07  156.619995  158.860001  156.110001  158.089996  152.768631   
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  
         Volume  Daily Returns  
  254  52059300       0.011905  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  ,
            Date        Open        High         Low       Close   Adj Close  \
  255 2019-01-08  159.539993  160.110001  157.199997  159.520004  154.150543   
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  
         Volume  Daily Returns  
  255  49388700       0.009046  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  ,
            Date        Open        High         Low       Close   Adj Close  \
  256 2019-01-09  160.139999  161.520004  159.470001  160.820007  155.406769   
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  
         Volume  Daily Returns  
  256  46491700       0.008149  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  ,
            Date        Open        High         Low       Close   Adj Close  \
  257 2019-01-10  159.600006  161.369995  158.699997  161.279999  155.851257   
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  
         Volume  Daily Returns  
  257  38943400       0.002860  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  ,
            Date        Open        High         Low       Close   Adj Close  \
  258 2019-01-11  160.330002  160.860001  159.789993  160.690002  155.281158   
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  
         Volume  Daily Returns  
  258  30176600      -0.003658  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  ,
            Date        Open        High         Low       Close   Adj Close  \
  259 2019-01-14  159.330002  159.960007  158.589996  159.270004  153.908905   
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  
         Volume  Daily Returns  
  259  30710200      -0.008837  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  ,
            Date        Open        High         Low       Close   Adj Close  \
  260 2019-01-15  160.000000  162.600006  159.910004  162.380005  156.914230   
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  
         Volume  Daily Returns  
  260  40874200       0.019527  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  ,
            Date        Open        High         Low       Close   Adj Close  \
  261 2019-01-16  162.649994  163.779999  162.289993  162.350006  156.885284   
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  
         Volume  Daily Returns  
  261  33812200      -0.000184  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  ,
            Date        Open        High         Low       Close   Adj Close  \
  262 2019-01-17  161.830002  164.360001  161.570007  163.630005  158.122238   
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  
         Volume  Daily Returns  
  262  39329000       0.007884  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  ,
            Date        Open        High         Low       Close   Adj Close  \
  263 2019-01-18  164.779999  166.020004  163.820007  165.250000  159.687637   
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  
         Volume  Daily Returns  
  263  57183200       0.009900  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  ,
            Date        Open        High         Low       Close   Adj Close  \
  264 2019-01-22  164.059998  164.139999  160.759995  161.940002  156.489059   
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  
         Volume  Daily Returns  
  264  56711700      -0.020030  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  ,
            Date        Open        High         Low       Close   Adj Close  \
  265 2019-01-23  162.770004  163.509995  160.320007  162.149994  156.691971   
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  
         Volume  Daily Returns  
  265  38106100       0.001297  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  ,
            Date        Open        High         Low       Close   Adj Close  \
  266 2019-01-24  162.679993  163.440002  162.059998  163.199997  157.706650   
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  
         Volume  Daily Returns  
  266  32417800       0.006476  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  ,
            Date        Open        High         Low       Close   Adj Close  \
  267 2019-01-25  164.509995  165.649994  163.949997  165.149994  159.590973   
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  
         Volume  Daily Returns  
  267  36515900       0.011948  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  ,
            Date        Open        High         Low       Close   Adj Close  \
  268 2019-01-28  163.020004  163.119995  161.750000  163.110001  157.619659   
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  
         Volume  Daily Returns  
  268  33491200      -0.012352  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  ,
            Date        Open        High         Low       Close   Adj Close  \
  269 2019-01-29  163.199997  163.240005  160.990005  161.570007  156.131516   
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  
         Volume  Daily Returns  
  269  30784200      -0.009441  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  ,
            Date        Open        High         Low       Close   Adj Close  \
  270 2019-01-30  163.399994  166.279999  162.889999  165.679993  160.103180   
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  
         Volume  Daily Returns  
  270  41346500       0.025438  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  ,
            Date        Open        High         Low       Close   Adj Close  \
  271 2019-01-31  166.699997  168.990005  166.470001  168.160004  162.499710   
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  
         Volume  Daily Returns  
  271  37258400       0.014969  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  ,
            Date        Open        High         Low       Close   Adj Close  \
  272 2019-02-01  167.330002  168.600006  166.990005  167.449997  161.813568   
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  
         Volume  Daily Returns  
  272  32143700      -0.004222  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  ,
            Date        Open        High         Low       Close   Adj Close  \
  273 2019-02-04  167.479996  169.529999  167.330002  169.529999  163.823593   
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  
         Volume  Daily Returns  
  273  26718800       0.012422  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  ,
            Date        Open        High         Low       Close   Adj Close  \
  274 2019-02-05  169.759995  171.229996  169.690002  171.029999  165.273071   
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  
         Volume  Daily Returns  
  274  28156400       0.008848  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  ,
            Date        Open        High         Low       Close   Adj Close  \
  275 2019-02-06  171.070007  171.369995  169.750000  170.520004  164.780304   
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  
         Volume  Daily Returns  
  275  27970000      -0.002982  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  ,
            Date        Open        High         Low       Close   Adj Close  \
  276 2019-02-07  169.029999  169.449997  166.949997  168.229996  162.567307   
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  
         Volume  Daily Returns  
  276  42036200      -0.013430  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  ,
            Date        Open        High         Low       Close   Adj Close  \
  277 2019-02-08  166.759995  168.589996  166.570007  168.559998  162.886215   
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  
         Volume  Daily Returns  
  277  29020700       0.001962  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  ,
            Date        Open        High         Low       Close   Adj Close  \
  278 2019-02-11  169.169998  169.580002  167.979996  168.399994  162.731567   
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  
         Volume  Daily Returns  
  278  21434100      -0.000949  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  ,
            Date        Open        High         Low       Close   Adj Close  \
  279 2019-02-12  169.630005  171.139999  169.330002  170.889999  165.137787   
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  
         Volume  Daily Returns  
  279  29722100       0.014786  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  ,
            Date        Open        High         Low       Close   Adj Close  \
  280 2019-02-13  171.649994  172.160004  170.820007  171.009995  165.253723   
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  
         Volume  Daily Returns  
  280  26094100       0.000702  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  ,
            Date        Open        High         Low       Close   Adj Close  \
  281 2019-02-14  170.399994  171.830002  169.830002  171.220001  165.456696   
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  
         Volume  Daily Returns  
  281  30326800       0.001228  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  ,
            Date        Open        High         Low       Close   Adj Close  \
  282 2019-02-15  172.520004  172.559998  171.139999  171.940002  166.152451   
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  
         Volume  Daily Returns  
  282  32521700       0.004205  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  ,
            Date        Open        High         Low       Close   Adj Close  \
  283 2019-02-19  171.410004  172.800003  171.380005  172.279999  166.481003   
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  
         Volume  Daily Returns  
  283  19487700       0.001977  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  ,
            Date        Open        High         Low       Close   Adj Close  \
  284 2019-02-20  172.399994  173.080002  171.320007  172.250000  166.452026   
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  
         Volume  Daily Returns  
  284  32593000      -0.000174  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  ,
            Date        Open        High         Low       Close   Adj Close  \
  285 2019-02-21  171.789993  172.259995  170.710007  171.619995  165.843201   
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  
         Volume  Daily Returns  
  285  25207400      -0.003658  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  ,
            Date        Open        High         Low       Close   Adj Close  \
  286 2019-02-22  171.990005  173.009995  171.899994  172.889999  167.070480   
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  
         Volume  Daily Returns  
  286  27735400       0.007400  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  ,
            Date        Open        High         Low       Close   Adj Close  \
  287 2019-02-25  174.210007  174.660004  173.399994  173.520004  167.679276   
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  
         Volume  Daily Returns  
  287  32608800       0.003644  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  ,
            Date        Open        High         Low       Close   Adj Close  \
  288 2019-02-26  173.100006  174.250000  172.809998  173.699997  167.853210   
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  
         Volume  Daily Returns  
  288  21939700       0.001037  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  ,
            Date        Open        High         Low       Close   Adj Close  \
  289 2019-02-27  172.899994  173.800003  171.759995  173.589996  167.746902   
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  
         Volume  Daily Returns  
  289  25162000      -0.000633  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  ,
            Date        Open        High         Low       Close   Adj Close  \
  290 2019-02-28  173.050003  173.809998  172.699997  173.190002  167.360413   
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  
         Volume  Daily Returns  
  290  25085500      -0.002304  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  ,
            Date        Open        High         Low       Close   Adj Close  \
  291 2019-03-01  174.440002  174.649994  173.179993  174.389999  168.519989   
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  
         Volume  Daily Returns  
  291  31431200       0.006929  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  ,
            Date        Open        High         Low       Close   Adj Close  \
  292 2019-03-04  175.539993  175.789993  172.470001  174.419998  168.548981   
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  
         Volume  Daily Returns  
  292  38063500       0.000172  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  ,
            Date        Open        High         Low       Close   Adj Close  \
  293 2019-03-05  174.550003  175.089996  173.690002  174.550003  168.674576   
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  
         Volume  Daily Returns  
  293  22319900       0.000745  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  ,
            Date        Open        High         Low       Close   Adj Close  \
  294 2019-03-06  174.720001  174.750000  173.279999  173.559998  167.717941   
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  
         Volume  Daily Returns  
  294  27194600      -0.005671  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  ,
            Date        Open        High         Low       Close   Adj Close  \
  295 2019-03-07  173.119995  173.179993  170.789993  171.429993  165.659622   
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  
         Volume  Daily Returns  
  295  39407400      -0.012273  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  ,
            Date        Open        High         Low       Close   Adj Close  \
  296 2019-03-08  169.509995  171.259995  169.339996  171.169998  165.408340   
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  
         Volume  Daily Returns  
  296  39303200      -0.001517  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  ,
            Date        Open        High         Low       Close   Adj Close  \
  297 2019-03-11  171.880005  174.850006  171.850006  174.729996  168.848541   
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  
         Volume  Daily Returns  
  297  30518400       0.020798  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  ,
            Date        Open        High         Low       Close   Adj Close  \
  298 2019-03-12  175.190002  176.139999  174.770004  175.690002  169.776260   
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  
         Volume  Daily Returns  
  298  33953500       0.005494  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  ,
            Date        Open        High         Low       Close   Adj Close  \
  299 2019-03-13  176.600006  177.929993  176.350006  177.009995  171.051788   
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  
         Volume  Daily Returns  
  299  42426100       0.007513  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  ,
            Date        Open        High         Low       Close   Adj Close  \
  300 2019-03-14  177.130005  177.339996  176.660004  176.710007  170.761917   
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  
         Volume  Daily Returns  
  300  23751500      -0.001695  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  ,
            Date        Open        High         Low       Close   Adj Close  \
  301 2019-03-15  177.399994  178.880005  177.279999  178.350006  172.346695   
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  
         Volume  Daily Returns  
  301  38192000       0.009281  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  ,
            Date        Open        High         Low       Close   Adj Close  \
  302 2019-03-18  177.949997  178.990005  177.589996  178.449997  172.757172   
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  
         Volume  Daily Returns  
  302  32935100       0.002382  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  ,
            Date        Open        High         Low       Close   Adj Close  \
  303 2019-03-19  179.179993  180.000000  178.289993  179.050003  173.338043   
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  
         Volume  Daily Returns  
  303  36893300       0.003362  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  ,
            Date        Open        High         Low       Close   Adj Close  \
  304 2019-03-20  179.059998  180.860001  178.240005  179.759995  174.025360   
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  
         Volume  Daily Returns  
  304  50105000       0.003965  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  ,
            Date        Open        High         Low       Close   Adj Close  \
  305 2019-03-21  179.220001  182.830002  179.199997  182.570007  176.745758   
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  
         Volume  Daily Returns  
  305  42428500       0.015632  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  ,
            Date        Open        High         Low       Close   Adj Close  \
  306 2019-03-22  181.779999  182.270004  178.369995  178.559998  172.863647   
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  
         Volume  Daily Returns  
  306  70794500      -0.021964  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  ,
            Date        Open        High         Low       Close   Adj Close  \
  307 2019-03-25  177.910004  178.839996  176.929993  178.220001  172.534485   
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  
         Volume  Daily Returns  
  307  46336500      -0.001904  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  ,
            Date        Open        High         Low       Close   Adj Close  \
  308 2019-03-26  179.600006  180.690002  178.139999  179.050003  173.338043   
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  
         Volume  Daily Returns  
  308  33248100       0.004657  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  ,
            Date        Open        High         Low       Close   Adj Close  \
  309 2019-03-27  179.320007  179.720001  176.600006  177.899994  172.224731   
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  
         Volume  Daily Returns  
  309  37096700      -0.006423  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  ,
            Date        Open        High         Low       Close   Adj Close  \
  310 2019-03-28  178.360001  178.979996  177.240005  178.309998  172.621643   
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  
         Volume  Daily Returns  
  310  30368200       0.002305  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  ,
            Date        Open        High         Low       Close   Adj Close  \
  311 2019-03-29  179.690002  179.830002  178.589996  179.660004  173.928558   
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  
         Volume  Daily Returns  
  311  35205500       0.007571  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  ,
            Date        Open        High         Low       Close   Adj Close  \
  312 2019-04-01  181.509995  182.259995  180.770004  182.039993  176.232666   
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  
         Volume  Daily Returns  
  312  30969500       0.013247  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  ,
            Date        Open        High         Low       Close   Adj Close  \
  313 2019-04-02  182.240005  182.910004  181.779999  182.729996  176.900620   
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  
         Volume  Daily Returns  
  313  22645200       0.003790  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  ,
            Date        Open        High         Low       Close   Adj Close  \
  314 2019-04-03  183.759995  184.919998  183.210007  183.779999  177.917130   
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  
         Volume  Daily Returns  
  314  31633500       0.005746  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  ,
            Date        Open        High         Low       Close   Adj Close  \
  315 2019-04-04  183.830002  184.500000  182.649994  183.710007  177.849350   
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  
         Volume  Daily Returns  
  315  28530800      -0.000381  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  ,
            Date        Open        High         Low       Close   Adj Close  \
  316 2019-04-05  184.240005  184.770004  184.020004  184.660004  178.769058   
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  
         Volume  Daily Returns  
  316  25674700       0.005171  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  ,
            Date        Open        High         Low       Close   Adj Close  \
  317 2019-04-08  184.360001  185.279999  183.630005  185.130005  179.224060   
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  
         Volume  Daily Returns  
  317  22697500       0.002545  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  ,
            Date        Open        High         Low       Close   Adj Close  \
  318 2019-04-09  184.500000  185.110001  184.089996  184.479996  178.594803   
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  
         Volume  Daily Returns  
  318  25631900      -0.003511  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  ,
            Date        Open        High         Low       Close   Adj Close  \
  319 2019-04-10  184.720001  185.529999  184.520004  185.470001  179.553238   
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  
         Volume  Daily Returns  
  319  24563000       0.005367  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  ,
            Date        Open        High         Low       Close   Adj Close  \
  320 2019-04-11  185.779999  185.779999  184.690002  185.029999  179.127243   
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  
         Volume  Daily Returns  
  320  20654100      -0.002373  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  ,
            Date        Open        High         Low       Close   Adj Close  \
  321 2019-04-12  185.850006  185.949997  185.059998  185.830002  179.901718   
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  
         Volume  Daily Returns  
  321  24989100       0.004324  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  ,
            Date        Open        High         Low       Close   Adj Close  \
  322 2019-04-15  185.839996  186.070007  184.619995  185.860001  179.930786   
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  
         Volume  Daily Returns  
  322  21073000       0.000162  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  ,
            Date        Open        High         Low       Close   Adj Close  \
  323 2019-04-16  186.539993  186.910004  185.929993  186.500000  180.550323   
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  
         Volume  Daily Returns  
  323  27195700       0.003443  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  ,
            Date        Open        High         Low       Close   Adj Close  \
  324 2019-04-17  187.750000  187.929993  186.600006  187.149994  181.179611   
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  
         Volume  Daily Returns  
  324  29651600       0.003485  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  ,
            Date        Open        High         Low       Close   Adj Close  \
  325 2019-04-18  187.460007  187.789993  186.289993  187.389999  181.411957   
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  
         Volume  Daily Returns  
  325  28580900       0.001282  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  ,
            Date        Open        High         Low       Close   Adj Close  \
  326 2019-04-22  186.570007  187.990005  186.429993  187.919998  181.925049   
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  
         Volume  Daily Returns  
  326  17936000       0.002828  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  ,
            Date        Open        High         Low       Close   Adj Close  \
  327 2019-04-23  188.399994  190.539993  188.130005  190.309998  184.238785   
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  
         Volume  Daily Returns  
  327  33665600       0.012718  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  ,
            Date        Open        High         Low       Close   Adj Close  \
  328 2019-04-24  190.470001  190.710007  189.649994  189.710007  183.657959   
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  
         Volume  Daily Returns  
  328  24977100      -0.003153  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  ,
            Date        Open        High         Low       Close   Adj Close  \
  329 2019-04-25  191.130005  191.220001  189.449997  190.479996  184.403366   
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  
         Volume  Daily Returns  
  329  29517500       0.004059  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  ,
            Date        Open        High         Low       Close   Adj Close  \
  330 2019-04-26  190.179993  190.690002  188.589996  190.649994  184.567917   
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  
         Volume  Daily Returns  
  330  26359500       0.000892  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  ,
            Date        Open        High         Low       Close   Adj Close  \
  331 2019-04-29  190.649994  191.320007  190.339996  191.020004  184.926178   
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  
         Volume  Daily Returns  
  331  21716200       0.001941  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  ,
            Date        Open        High         Low       Close   Adj Close  \
  332 2019-04-30  189.479996  189.850006  188.210007  189.539993  183.493362   
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  
         Volume  Daily Returns  
  332  31495300      -0.007748  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  ,
            Date        Open        High         Low       Close   Adj Close  \
  333 2019-05-01  190.779999  191.320007  188.800003  188.929993  182.902817   
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  
         Volume  Daily Returns  
  333  34797100      -0.003218  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  ,
            Date        Open        High         Low       Close   Adj Close  \
  334 2019-05-02  188.869995  189.850006  186.869995  188.110001  182.108948   
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  
         Volume  Daily Returns  
  334  44110100      -0.004340  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  ,
            Date        Open        High         Low       Close   Adj Close  \
  335 2019-05-03  189.669998  191.250000  189.330002  191.110001  185.013275   
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  
         Volume  Daily Returns  
  335  30386200       0.015948  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  ,
            Date        Open        High         Low       Close   Adj Close  \
  336 2019-05-06  187.050003  190.199997  186.759995  189.940002  183.880615   
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  
         Volume  Daily Returns  
  336  38371800      -0.006122  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  ,
            Date        Open        High         Low       Close   Adj Close  \
  337 2019-05-07  187.869995  188.669998  184.509995  186.240005  180.298645   
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  
         Volume  Daily Returns  
  337  58818100      -0.019480  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  ,
            Date        Open        High         Low       Close   Adj Close  \
  338 2019-05-08  185.630005  187.169998  184.960007  185.770004  179.843643   
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  
         Volume  Daily Returns  
  338  37165300      -0.002524  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  ,
            Date        Open        High         Low       Close   Adj Close  \
  339 2019-05-09  183.699997  185.410004  182.089996  184.770004  178.875549   
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  
         Volume  Daily Returns  
  339  55351700      -0.005383  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  ,
            Date        Open        High         Low       Close   Adj Close  \
  340 2019-05-10  184.110001  185.889999  181.029999  185.000000  179.098267   
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  
         Volume  Daily Returns  
  340  58526400       0.001245  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  ,
            Date        Open        High         Low       Close   Adj Close  \
  341 2019-05-13  180.289993  181.259995  178.059998  178.580002  172.882980   
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  
         Volume  Daily Returns  
  341  67185800      -0.034703  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  ,
            Date        Open        High         Low       Close   Adj Close  \
  342 2019-05-14  179.520004  181.630005  178.860001  180.539993  174.780487   
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  
         Volume  Daily Returns  
  342  43360600       0.010976  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  ,
            Date        Open        High         Low       Close   Adj Close  \
  343 2019-05-15  179.350006  183.550003  179.309998  183.089996  177.249115   
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  
         Volume  Daily Returns  
  343  40944500       0.014124  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  ,
            Date        Open        High         Low       Close   Adj Close  \
  344 2019-05-16  183.169998  186.070007  182.949997  184.929993  179.030441   
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  
         Volume  Daily Returns  
  344  39281200       0.010050  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  ,
            Date        Open        High         Low       Close   Adj Close  \
  345 2019-05-17  183.100006  185.580002  182.880005  183.039993  177.200714   
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  
         Volume  Daily Returns  
  345  44702300      -0.010220  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  ,
            Date        Open        High         Low       Close   Adj Close  \
  346 2019-05-20  180.490005  181.179993  179.339996  179.949997  174.209320   
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  
         Volume  Daily Returns  
  346  38608300      -0.016881  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  ,
            Date        Open        High         Low       Close   Adj Close  \
  347 2019-05-21  181.500000  182.330002  180.919998  181.830002  176.029343   
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  
         Volume  Daily Returns  
  347  31613800       0.010447  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  ,
            Date        Open        High         Low       Close   Adj Close  \
  348 2019-05-22  180.820007  182.070007  180.750000  181.020004  175.245178   
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  
         Volume  Daily Returns  
  348  24332600      -0.004455  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  ,
            Date        Open        High         Low       Close   Adj Close  \
  349 2019-05-23  178.940002  179.020004  177.139999  178.250000  172.563538   
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  
         Volume  Daily Returns  
  349  45351300      -0.015302  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  ,
            Date        Open        High         Low       Close   Adj Close  \
  350 2019-05-24  179.210007  179.850006  177.940002  178.160004  172.476471   
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  
         Volume  Daily Returns  
  350  25903300      -0.000505  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  ,
            Date        Open        High         Low       Close   Adj Close  \
  351 2019-05-28  178.660004  179.660004  177.470001  177.490005  171.827759   
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  
         Volume  Daily Returns  
  351  24763800      -0.003761  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  ,
            Date        Open        High         Low       Close   Adj Close  \
  352 2019-05-29  176.389999  177.000000  175.089996  176.029999  170.414368   
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  
         Volume  Daily Returns  
  352  42178800      -0.008226  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  ,
            Date        Open        High         Low       Close   Adj Close  \
  353 2019-05-30  176.500000  177.270004  175.770004  176.770004  171.130783   
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  
         Volume  Daily Returns  
  353  30354800       0.004204  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  ,
            Date        Open        High         Low       Close   Adj Close  \
  354 2019-05-31  174.690002  175.289993  173.869995  173.949997  168.400696   
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  
         Volume  Daily Returns  
  354  45446200      -0.015953  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  ,
            Date        Open        High         Low       Close   Adj Close  \
  355 2019-06-03  173.479996  173.949997  169.270004  170.119995  164.692871   
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  
         Volume  Daily Returns  
  355  75842300      -0.022018  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  ,
            Date        Open        High         Low       Close   Adj Close  \
  356 2019-06-04  172.029999  174.970001  171.369995  174.910004  169.330093   
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  
         Volume  Daily Returns  
  356  47797800       0.028157  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  ,
            Date        Open        High         Low       Close   Adj Close  \
  357 2019-06-05  176.580002  176.610001  174.380005  176.210007  170.588623   
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  
         Volume  Daily Returns  
  357  34412700       0.007432  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  ,
            Date        Open        High         Low       Close   Adj Close  \
  358 2019-06-06  176.509995  178.039993  175.729996  177.610001  171.943954   
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  
         Volume  Daily Returns  
  358  29913200       0.007945  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  ,
            Date        Open        High         Low       Close   Adj Close  \
  359 2019-06-07  178.559998  181.770004  178.330002  181.039993  175.264526   
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  
         Volume  Daily Returns  
  359  45888300       0.019312  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  ,
            Date        Open        High         Low       Close   Adj Close  \
  360 2019-06-10  182.250000  184.850006  182.210007  183.149994  177.307251   
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  
         Volume  Daily Returns  
  360  41385300       0.011655  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  ,
            Date        Open        High         Low       Close   Adj Close  \
  361 2019-06-11  185.059998  185.399994  182.779999  183.399994  177.549240   
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  
         Volume  Daily Returns  
  361  41260300       0.001365  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  ,
            Date        Open        High         Low       Close   Adj Close  \
  362 2019-06-12  182.899994  183.279999  182.000000  182.339996  176.523056   
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  
         Volume  Daily Returns  
  362  27758100      -0.005780  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  ,
            Date        Open        High         Low       Close   Adj Close  \
  363 2019-06-13  183.100006  183.869995  182.740005  183.419998  177.568573   
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  
         Volume  Daily Returns  
  363  23715800       0.005923  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  ,
            Date        Open        High         Low       Close   Adj Close  \
  364 2019-06-14  182.479996  183.110001  181.940002  182.639999  176.813492   
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  
         Volume  Daily Returns  
  364  22844100      -0.004252  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  ,
            Date        Open        High         Low       Close   Adj Close  \
  365 2019-06-17  183.039993  184.250000  182.839996  183.740005  177.878433   
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  
         Volume  Daily Returns  
  365  20379500       0.006023  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  ,
            Date        Open        High         Low       Close   Adj Close  \
  366 2019-06-18  185.910004  187.720001  185.429993  186.410004  180.463257   
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  
         Volume  Daily Returns  
  366  48177300       0.014531  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  ,
            Date        Open        High         Low       Close   Adj Close  \
  367 2019-06-19  186.660004  187.529999  185.570007  187.110001  181.140869   
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  
         Volume  Daily Returns  
  367  31672900       0.003755  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  ,
            Date        Open        High         Low       Close   Adj Close  \
  368 2019-06-20  189.720001  189.759995  187.160004  188.850006  182.825378   
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  
         Volume  Daily Returns  
  368  40922000       0.009299  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  ,
            Date        Open        High         Low       Close   Adj Close  \
  369 2019-06-21  188.630005  189.770004  188.169998  188.570007  182.554352   
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  
         Volume  Daily Returns  
  369  39980400      -0.001482  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  ,
            Date        Open        High         Low       Close   Adj Close  \
  370 2019-06-24  188.529999  188.720001  188.059998  188.160004  182.560150   
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  
         Volume  Daily Returns  
  370  19375200       0.000032  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  ,
            Date        Open        High         Low       Close   Adj Close  \
  371 2019-06-25  188.029999  188.139999  184.649994  184.929993  179.426254   
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  
         Volume  Daily Returns  
  371  33921100      -0.017166  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  ,
            Date        Open        High         Low       Close   Adj Close  \
  372 2019-06-26  186.160004  187.330002  185.490005  185.789993  180.260651   
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  
         Volume  Daily Returns  
  372  22595700       0.004650  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  ,
            Date        Open        High         Low       Close   Adj Close  \
  373 2019-06-27  186.460007  186.940002  185.990005  186.500000  180.949539   
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  
         Volume  Daily Returns  
  373  19709200       0.003822  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  ,
            Date        Open        High         Low       Close   Adj Close  \
  374 2019-06-28  186.949997  187.149994  186.070007  186.740005  181.182419   
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  
         Volume  Daily Returns  
  374  21179200       0.001287  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  ,
            Date        Open        High         Low       Close   Adj Close  \
  375 2019-07-01  190.320007  190.570007  188.380005  189.259995  183.627411   
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  
         Volume  Daily Returns  
  375  31025600       0.013495  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  ,
            Date        Open        High         Low       Close   Adj Close  \
  376 2019-07-02  189.199997  190.029999  188.660004  190.009995  184.355087   
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  
         Volume  Daily Returns  
  376  18035800       0.003963  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  ,
            Date        Open        High         Low       Close   Adj Close  \
  377 2019-07-03  190.490005  191.440002  190.289993  191.440002  185.742538   
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  
         Volume  Daily Returns  
  377  15792100       0.007526  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  ,
            Date        Open        High         Low       Close   Adj Close  \
  378 2019-07-05  190.130005  191.399994  189.389999  191.050003  185.364151   
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  
         Volume  Daily Returns  
  378  21415600      -0.002037  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  ,
            Date        Open        High         Low       Close   Adj Close  \
  379 2019-07-08  189.809998  189.869995  188.929993  189.710007  184.064011   
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  
         Volume  Daily Returns  
  379  17598800      -0.007014  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  ,
            Date        Open        High         Low       Close   Adj Close  \
  380 2019-07-09  188.809998  190.899994  188.649994  190.660004  184.985794   
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  
         Volume  Daily Returns  
  380  19193500       0.005008  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  ,
            Date        Open        High         Low       Close   Adj Close  \
  381 2019-07-10  191.820007  193.089996  191.470001  192.559998  186.829208   
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  
         Volume  Daily Returns  
  381  28374500       0.009965  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  ,
            Date        Open        High         Low       Close   Adj Close  \
  382 2019-07-11  192.850006  193.339996  191.809998  192.419998  186.693359   
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  
         Volume  Daily Returns  
  382  23736100      -0.000727  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  ,
            Date        Open        High         Low       Close   Adj Close  \
  383 2019-07-12  192.630005  193.539993  192.449997  193.529999  187.770370   
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  
         Volume  Daily Returns  
  383  20211900       0.005769  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  ,
            Date        Open        High         Low       Close   Adj Close  \
  384 2019-07-15  193.979996  194.190002  193.440002  194.149994  188.371887   
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  
         Volume  Daily Returns  
  384  15606100       0.003203  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  ,
            Date        Open        High         Low       Close   Adj Close  \
  385 2019-07-16  193.910004  194.089996  192.559998  193.149994  187.401657   
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  
         Volume  Daily Returns  
  385  20190900      -0.005151  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  ,
            Date        Open        High         Low       Close   Adj Close  \
  386 2019-07-17  193.149994  193.490005  192.179993  192.199997  186.479904   
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  
         Volume  Daily Returns  
  386  16765100      -0.004919  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  ,
            Date        Open        High         Low       Close   Adj Close  \
  387 2019-07-18  191.289993  192.789993  190.690002  192.419998  186.693359   
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  
         Volume  Daily Returns  
  387  28877000       0.001145  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  ,
            Date        Open        High         Low       Close   Adj Close  \
  388 2019-07-19  193.740005  193.830002  190.809998  191.009995  185.325317   
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  
         Volume  Daily Returns  
  388  29387900      -0.007328  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  ,
            Date        Open        High         Low       Close   Adj Close  \
  389 2019-07-22  191.440002  192.940002  191.440002  192.529999  186.800079   
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  
         Volume  Daily Returns  
  389  18954900       0.007958  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  ,
            Date        Open        High         Low       Close   Adj Close  \
  390 2019-07-23  193.580002  193.809998  192.289993  193.789993  188.022552   
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  
         Volume  Daily Returns  
  390  23786700       0.006544  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  ,
            Date        Open        High         Low       Close   Adj Close  \
  391 2019-07-24  193.050003  195.160004  193.029999  195.149994  189.342087   
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  
         Volume  Daily Returns  
  391  20422900       0.007018  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  ,
            Date        Open        High         Low       Close   Adj Close  \
  392 2019-07-25  194.490005  194.520004  192.929993  193.300003  187.547150   
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  
         Volume  Daily Returns  
  392  23434700      -0.009480  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  ,
            Date        Open        High         Low       Close   Adj Close  \
  393 2019-07-26  194.529999  195.550003  194.429993  195.289993  189.477936   
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  
         Volume  Daily Returns  
  393  20431200       0.010295  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  ,
            Date        Open        High         Low       Close   Adj Close  \
  394 2019-07-29  195.110001  195.179993  193.389999  194.619995  188.827850   
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  
         Volume  Daily Returns  
  394  20451700      -0.003431  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  ,
            Date        Open        High         Low       Close   Adj Close  \
  395 2019-07-30  193.130005  194.539993  192.990005  193.779999  188.012894   
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  
         Volume  Daily Returns  
  395  18705000      -0.004316  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  ,
            Date        Open        High         Low       Close   Adj Close  \
  396 2019-07-31  194.300003  194.429993  189.320007  191.100006  185.412628   
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  
         Volume  Daily Returns  
  396  41627500      -0.013830  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  ,
            Date        Open        High         Low       Close   Adj Close  \
  397 2019-08-01  191.429993  194.979996  189.229996  190.149994  184.490891   
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  
         Volume  Daily Returns  
  397  63251600      -0.004971  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  ,
            Date        Open        High         Low       Close   Adj Close  \
  398 2019-08-02  188.720001  188.990005  186.210007  187.350006  181.774246   
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  
         Volume  Daily Returns  
  398  55214000      -0.014725  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  ,
            Date        Open        High         Low       Close   Adj Close  \
  399 2019-08-05  183.429993  183.509995  179.199997  180.729996  175.351257   
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  
         Volume  Daily Returns  
  399  75040000      -0.035335  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  ,
            Date        Open        High         Low       Close   Adj Close  \
  400 2019-08-06  182.399994  183.800003  181.070007  183.259995  177.805954   
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  
         Volume  Daily Returns  
  400  41897200       0.013999  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  ,
            Date        Open        High         Low       Close   Adj Close  \
  401 2019-08-07  181.270004  184.509995  179.889999  184.250000  178.766495   
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  
         Volume  Daily Returns  
  401  49990600       0.005402  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  ,
            Date        Open        High         Low       Close   Adj Close  \
  402 2019-08-08  185.080002  188.320007  184.570007  188.259995  182.657150   
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  
         Volume  Daily Returns  
  402  38418100       0.021764  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  ,
            Date        Open        High         Low       Close   Adj Close  \
  403 2019-08-09  187.360001  188.000000  185.029999  186.490005  180.939880   
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  
         Volume  Daily Returns  
  403  33608900      -0.009402  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  ,
            Date        Open        High         Low       Close   Adj Close  \
  404 2019-08-12  185.339996  185.899994  183.500000  184.350006  178.863556   
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  
         Volume  Daily Returns  
  404  24642900      -0.011475  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  ,
            Date        Open        High         Low       Close   Adj Close  \
  405 2019-08-13  184.190002  189.679993  184.020004  188.389999  182.783295   
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  
         Volume  Daily Returns  
  405  40241900       0.021915  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  ,
            Date        Open        High         Low       Close   Adj Close  \
  406 2019-08-14  185.360001  185.949997  182.419998  182.759995  177.320831   
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  
         Volume  Daily Returns  
  406  51000500      -0.029885  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  ,
            Date        Open        High         Low       Close   Adj Close  \
  407 2019-08-15  183.000000  183.589996  181.160004  182.550003  177.117081   
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  
         Volume  Daily Returns  
  407  36685000      -0.001149  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  ,
            Date        Open        High         Low       Close   Adj Close  \
  408 2019-08-16  184.210007  185.949997  184.100006  185.479996  179.959900   
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  
         Volume  Daily Returns  
  408  32781400       0.016051  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  ,
            Date        Open        High         Low       Close   Adj Close  \
  409 2019-08-19  188.160004  188.830002  187.500000  188.429993  182.822113   
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  
         Volume  Daily Returns  
  409  22494100       0.015905  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  ,
            Date        Open        High         Low       Close   Adj Close  \
  410 2019-08-20  187.960007  188.639999  186.919998  186.970001  181.405579   
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  
         Volume  Daily Returns  
  410  19902900      -0.007748  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  ,
            Date        Open        High         Low       Close   Adj Close  \
  411 2019-08-21  188.610001  189.229996  187.960007  188.630005  183.016174   
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  
         Volume  Daily Returns  
  411  20418500       0.008878  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  ,
            Date        Open        High         Low       Close   Adj Close  \
  412 2019-08-22  188.979996  189.460007  186.539993  188.020004  182.424332   
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  
         Volume  Daily Returns  
  412  24243700      -0.003234  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  ,
            Date        Open        High         Low       Close   Adj Close  \
  413 2019-08-23  186.740005  188.449997  181.559998  182.070007  176.651382   
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  
         Volume  Daily Returns  
  413  55372400      -0.031646  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  ,
            Date        Open        High         Low       Close   Adj Close  \
  414 2019-08-26  184.139999  184.869995  183.080002  184.820007  179.319550   
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  
         Volume  Daily Returns  
  414  27598900       0.015104  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  ,
            Date        Open        High         Low       Close   Adj Close  \
  415 2019-08-27  186.110001  186.419998  183.710007  184.429993  178.941116   
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  
         Volume  Daily Returns  
  415  28012800      -0.002110  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  ,
            Date        Open        High         Low       Close   Adj Close  \
  416 2019-08-28  183.830002  185.399994  182.910004  185.089996  179.581482   
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  
         Volume  Daily Returns  
  416  21792400       0.003579  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  ,
            Date        Open        High         Low       Close   Adj Close  \
  417 2019-08-29  187.389999  188.460007  186.679993  187.919998  182.327271   
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  
         Volume  Daily Returns  
  417  25358900       0.015290  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  ,
            Date        Open        High         Low       Close   Adj Close  \
  418 2019-08-30  188.929993  188.970001  186.410004  187.470001  181.890686   
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  
         Volume  Daily Returns  
  418  26319800      -0.002395  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  ,
            Date        Open        High         Low       Close   Adj Close  \
  419 2019-09-03  186.220001  187.179993  185.029999  185.649994  180.124832   
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  
         Volume  Daily Returns  
  419  27964200      -0.009708  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  ,
            Date        Open        High         Low       Close   Adj Close  \
  420 2019-09-04  187.440002  188.490005  186.899994  188.330002  182.725067   
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  
         Volume  Daily Returns  
  420  21592100       0.014436  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  ,
            Date        Open        High         Low       Close   Adj Close  \
  421 2019-09-05  190.410004  192.330002  190.339996  191.779999  186.072403   
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  
         Volume  Daily Returns  
  421  33932600       0.018319  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  ,
            Date        Open        High         Low       Close   Adj Close  \
  422 2019-09-06  192.100006  192.169998  191.169998  191.589996  185.888062   
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  
         Volume  Daily Returns  
  422  19487800      -0.000991  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  ,
            Date        Open        High         Low       Close   Adj Close  \
  423 2019-09-09  192.190002  192.270004  190.220001  191.190002  185.499969   
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  
         Volume  Daily Returns  
  423  24407600      -0.002088  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  ,
            Date        Open        High         Low       Close   Adj Close  \
  424 2019-09-10  190.160004  190.740005  188.910004  190.639999  184.966309   
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  
         Volume  Daily Returns  
  424  23744700      -0.002877  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  ,
            Date        Open        High         Low       Close   Adj Close  \
  425 2019-09-11  191.000000  192.529999  190.559998  192.429993  186.703049   
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  
         Volume  Daily Returns  
  425  25063600       0.009389  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  ,
            Date        Open        High         Low       Close   Adj Close  \
  426 2019-09-12  193.610001  194.710007  192.970001  193.229996  187.479248   
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  
         Volume  Daily Returns  
  426  28689900       0.004157  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  ,
            Date        Open        High         Low       Close   Adj Close  \
  427 2019-09-13  192.949997  193.399994  192.289993  192.539993  186.809784   
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  
         Volume  Daily Returns  
  427  27669800      -0.003571  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  ,
            Date        Open        High         Low       Close   Adj Close  \
  428 2019-09-16  191.300003  192.080002  191.110001  191.679993  185.975388   
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  
         Volume  Daily Returns  
  428  20319000      -0.004467  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  ,
            Date        Open        High         Low       Close   Adj Close  \
  429 2019-09-17  191.699997  192.600006  191.289993  192.600006  186.868011   
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  
         Volume  Daily Returns  
  429  20953400       0.004800  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  ,
            Date        Open        High         Low       Close   Adj Close  \
  430 2019-09-18  192.199997  192.600006  190.110001  192.520004  186.790405   
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  
         Volume  Daily Returns  
  430  29781300      -0.000415  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  ,
            Date        Open        High         Low       Close   Adj Close  \
  431 2019-09-19  192.860001  194.039993  192.470001  192.839996  187.100845   
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  
         Volume  Daily Returns  
  431  26039400       0.001662  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  ,
            Date        Open        High         Low       Close   Adj Close  \
  432 2019-09-20  193.110001  193.309998  190.160004  190.800003  185.121536   
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  
         Volume  Daily Returns  
  432  29086100      -0.010579  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  ,
            Date        Open        High         Low       Close   Adj Close  \
  433 2019-09-23  190.360001  191.070007  189.720001  190.500000  185.203247   
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  
         Volume  Daily Returns  
  433  22485900       0.000441  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  ,
            Date        Open        High         Low       Close   Adj Close  \
  434 2019-09-24  191.369995  191.789993  187.149994  187.970001  182.743607   
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  
         Volume  Daily Returns  
  434  40820700      -0.013281  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  ,
            Date        Open        High         Low       Close   Adj Close  \
  435 2019-09-25  187.779999  190.580002  186.210007  190.080002  184.794922   
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  
         Volume  Daily Returns  
  435  34704900       0.011225  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  ,
            Date        Open        High         Low       Close   Adj Close  \
  436 2019-09-26  189.830002  190.000000  187.979996  189.380005  184.114365   
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  
         Volume  Daily Returns  
  436  26826000      -0.003683  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  ,
            Date        Open        High         Low       Close   Adj Close  \
  437 2019-09-27  189.729996  189.830002  185.750000  187.029999  181.829712   
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  
         Volume  Daily Returns  
  437  40773500      -0.012409  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  ,
            Date        Open        High         Low       Close   Adj Close  \
  438 2019-09-30  187.789993  189.110001  187.399994  188.809998  183.560196   
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  
         Volume  Daily Returns  
  438  26307700       0.009517  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  ,
            Date        Open        High         Low       Close   Adj Close  \
  439 2019-10-01  189.500000  190.589996  186.960007  187.270004  182.063049   
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  
         Volume  Daily Returns  
  439  32367600      -0.008156  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  ,
            Date        Open        High         Low       Close   Adj Close  \
  440 2019-10-02  186.000000  186.029999  183.020004  184.050003  178.932571   
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  
         Volume  Daily Returns  
  440  48544300      -0.017194  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  ,
            Date        Open        High         Low       Close   Adj Close  \
  441 2019-10-03  184.029999  186.210007  181.820007  186.070007  180.896362   
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  
         Volume  Daily Returns  
  441  39392500       0.010975  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  ,
            Date        Open        High         Low       Close   Adj Close  \
  442 2019-10-04  187.080002  189.080002  186.880005  188.809998  183.560196   
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  
         Volume  Daily Returns  
  442  31887600       0.014726  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  ,
            Date        Open        High         Low       Close   Adj Close  \
  443 2019-10-07  188.270004  189.740005  187.910004  188.240005  183.006058   
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  
         Volume  Daily Returns  
  443  21216000      -0.003019  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  ,
            Date        Open        High         Low       Close   Adj Close  \
  444 2019-10-08  187.059998  187.860001  185.270004  185.419998  180.264465   
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  
         Volume  Daily Returns  
  444  32379300      -0.014981  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  ,
            Date        Open        High         Low       Close   Adj Close  \
  445 2019-10-09  186.990005  188.080002  186.429993  187.229996  182.024139   
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  
         Volume  Daily Returns  
  445  20147400       0.009762  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  ,
            Date        Open        High         Low       Close   Adj Close  \
  446 2019-10-10  187.279999  189.429993  187.119995  188.679993  183.433823   
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  
         Volume  Daily Returns  
  446  25177700       0.007744  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  ,
            Date        Open        High         Low       Close   Adj Close  \
  447 2019-10-11  190.830002  192.630005  190.720001  191.110001  185.796249   
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  
         Volume  Daily Returns  
  447  40976700       0.012879  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  ,
            Date        Open        High         Low       Close   Adj Close  \
  448 2019-10-14  190.839996  191.699997  190.649994  191.089996  185.776855   
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  
         Volume  Daily Returns  
  448  14975000      -0.000104  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  ,
            Date        Open        High         Low       Close   Adj Close  \
  449 2019-10-15  191.679993  193.970001  191.559998  193.520004  188.139267   
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  
         Volume  Daily Returns  
  449  23234200       0.012716  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  ,
            Date        Open        High         Low       Close   Adj Close  \
  450 2019-10-16  192.860001  193.529999  192.429993  193.039993  187.672623   
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  
         Volume  Daily Returns  
  450  20457100      -0.002480  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  ,
            Date        Open        High         Low       Close   Adj Close  \
  451 2019-10-17  194.199997  194.500000  192.809998  193.550003  188.168457   
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  
         Volume  Daily Returns  
  451  19045200       0.002642  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  ,
            Date        Open        High         Low       Close   Adj Close  \
  452 2019-10-18  193.199997  193.669998  190.710007  191.690002  186.360138   
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  
         Volume  Daily Returns  
  452  27700800      -0.009610  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  ,
            Date        Open        High         Low       Close   Adj Close  \
  453 2019-10-21  192.710007  193.520004  192.139999  193.389999  188.012863   
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  
         Volume  Daily Returns  
  453  15801200       0.008868  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  ,
            Date        Open        High         Low       Close   Adj Close  \
  454 2019-10-22  194.149994  194.419998  191.789993  191.850006  186.515701   
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  
         Volume  Daily Returns  
  454  22392300      -0.007963  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  ,
            Date        Open        High         Low       Close   Adj Close  \
  455 2019-10-23  191.460007  192.259995  191.149994  192.220001  186.875412   
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  
         Volume  Daily Returns  
  455  14828400       0.001929  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  ,
            Date        Open        High         Low       Close   Adj Close  \
  456 2019-10-24  193.589996  194.210007  192.740005  194.089996  188.693405   
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  
         Volume  Daily Returns  
  456  18998500       0.009728  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  ,
            Date        Open        High         Low       Close   Adj Close  \
  457 2019-10-25  193.089996  195.740005  193.050003  195.639999  190.200302   
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  
         Volume  Daily Returns  
  457  21507100       0.007986  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  ,
            Date        Open        High         Low       Close   Adj Close  \
  458 2019-10-28  196.550003  197.830002  196.550003  197.570007  192.076675   
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  
         Volume  Daily Returns  
  458  18818700       0.009865  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  ,
            Date        Open        High         Low       Close   Adj Close  \
  459 2019-10-29  197.240005  197.539993  196.009995  196.039993  190.589172   
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  
         Volume  Daily Returns  
  459  18569700      -0.007744  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  ,
            Date        Open        High         Low       Close   Adj Close  \
  460 2019-10-30  196.419998  197.320007  195.289993  196.990005  191.512787   
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  
         Volume  Daily Returns  
  460  21764300       0.004846  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  ,
            Date        Open        High         Low       Close   Adj Close  \
  461 2019-10-31  197.559998  197.649994  195.940002  197.080002  191.600250   
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  
         Volume  Daily Returns  
  461  26801800       0.000457  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  ,
            Date        Open        High         Low       Close   Adj Close  \
  462 2019-11-01  197.929993  198.880005  197.630005  198.869995  193.340500   
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  
         Volume  Daily Returns  
  462  22131900       0.009083  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  ,
            Date        Open        High         Low       Close   Adj Close  \
  463 2019-11-04  200.190002  200.529999  198.869995  200.100006  194.536316   
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  
         Volume  Daily Returns  
  463  19015900       0.006185  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  ,
            Date        Open        High         Low       Close   Adj Close  \
  464 2019-11-05  200.350006  200.550003  199.550003  200.210007  194.643234   
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  
         Volume  Daily Returns  
  464  15048900       0.000550  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  ,
            Date        Open        High         Low       Close   Adj Close  \
  465 2019-11-06  199.979996  200.000000  198.789993  199.759995  194.205780   
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  
         Volume  Daily Returns  
  465  19725500      -0.002247  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  ,
            Date        Open        High         Low       Close   Adj Close  \
  466 2019-11-07  200.759995  201.720001  199.850006  200.429993  194.857117   
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  
         Volume  Daily Returns  
  466  17832400       0.003354  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  ,
            Date        Open        High         Low       Close   Adj Close  \
  467 2019-11-08  200.070007  201.250000  199.539993  201.229996  195.634888   
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  
         Volume  Daily Returns  
  467  15258800       0.003991  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  ,
            Date        Open        High         Low       Close   Adj Close  \
  468 2019-11-11  200.210007  201.039993  199.940002  200.960007  195.372391   
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  
         Volume  Daily Returns  
  468  10147600      -0.001342  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  ,
            Date        Open        High         Low       Close   Adj Close  \
  469 2019-11-12  201.130005  202.210007  200.820007  201.539993  195.936234   
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  
         Volume  Daily Returns  
  469  14778300       0.002886  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  ,
            Date        Open        High         Low       Close   Adj Close  \
  470 2019-11-13  200.839996  201.779999  200.710007  201.589996  195.984863   
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  
         Volume  Daily Returns  
  470  15774600       0.000248  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  ,
            Date        Open        High         Low       Close   Adj Close  \
  471 2019-11-14  200.830002  201.559998  200.220001  201.429993  195.829315   
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  
         Volume  Daily Returns  
  471  16945400      -0.000794  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  ,
            Date        Open        High         Low       Close   Adj Close  \
  472 2019-11-15  202.649994  202.910004  202.000000  202.910004  197.268188   
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  
         Volume  Daily Returns  
  472  18427900       0.007348  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  ,
            Date        Open        High         Low       Close   Adj Close  \
  473 2019-11-18  202.589996  203.389999  201.770004  203.070007  197.423706   
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  
         Volume  Daily Returns  
  473  18365900       0.000788  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  ,
            Date        Open        High         Low       Close   Adj Close  \
  474 2019-11-19  203.839996  203.839996  202.589996  203.369995  197.715393   
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  
         Volume  Daily Returns  
  474  16923300       0.001477  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  ,
            Date        Open        High         Low       Close   Adj Close  \
  475 2019-11-20  202.839996  203.449997  200.619995  202.149994  196.529282   
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  
         Volume  Daily Returns  
  475  36629000      -0.005999  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  ,
            Date        Open        High         Low       Close   Adj Close  \
  476 2019-11-21  201.929993  202.070007  201.070007  201.699997  196.091797   
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  
         Volume  Daily Returns  
  476  17883600      -0.002226  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  ,
            Date        Open        High         Low       Close   Adj Close  \
  477 2019-11-22  202.199997  202.320007  200.740005  201.830002  196.218216   
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  
         Volume  Daily Returns  
  477  17189600       0.000645  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  ,
            Date        Open        High         Low       Close   Adj Close  \
  478 2019-11-25  202.699997  204.259995  202.669998  204.220001  198.541748   
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  
         Volume  Daily Returns  
  478  17752800       0.011842  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  ,
            Date        Open        High         Low       Close   Adj Close  \
  479 2019-11-26  204.350006  204.869995  204.050003  204.610001  198.920898   
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  
         Volume  Daily Returns  
  479  14780600       0.001910  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  ,
            Date        Open        High         Low       Close   Adj Close  \
  480 2019-11-27  205.139999  206.050003  204.889999  206.039993  200.311157   
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  
         Volume  Daily Returns  
  480  16963100       0.006989  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  ,
            Date        Open        High         Low       Close   Adj Close  \
  481 2019-11-29  205.520004  205.830002  205.000000  205.100006  199.397278   
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  
         Volume  Daily Returns  
  481   9854600      -0.004562  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  ,
            Date        Open        High         Low       Close   Adj Close  \
  482 2019-12-02  205.110001  205.179993  201.779999  203.000000  197.355682   
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  
         Volume  Daily Returns  
  482  28007000      -0.010239  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  ,
            Date        Open        High         Low       Close   Adj Close  \
  483 2019-12-03  200.210007  201.490005  199.229996  201.410004  195.809845   
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  
         Volume  Daily Returns  
  483  31104100      -0.007833  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  ,
            Date        Open        High         Low       Close   Adj Close  \
  484 2019-12-04  202.440002  202.910004  202.139999  202.429993  196.801514   
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  
         Volume  Daily Returns  
  484  15300100       0.005064  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  ,
            Date        Open        High         Low       Close   Adj Close  \
  485 2019-12-05  203.149994  203.149994  201.839996  202.830002  197.190369   
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  
         Volume  Daily Returns  
  485  14962300       0.001976  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  ,
            Date        Open        High         Low       Close   Adj Close  \
  486 2019-12-06  204.309998  205.149994  204.149994  205.000000  199.300095   
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  
         Volume  Daily Returns  
  486  16555300       0.010699  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  ,
            Date        Open        High         Low       Close   Adj Close  \
  487 2019-12-09  204.630005  205.589996  203.979996  204.070007  198.395935   
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  
         Volume  Daily Returns  
  487  13984100      -0.004537  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  ,
            Date        Open        High         Low       Close   Adj Close  \
  488 2019-12-10  204.169998  204.880005  203.440002  203.899994  198.230652   
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  
         Volume  Daily Returns  
  488  21799800      -0.000833  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  ,
            Date        Open        High         Low       Close   Adj Close  \
  489 2019-12-11  204.360001  205.190002  204.039993  204.979996  199.280624   
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  
         Volume  Daily Returns  
  489  18780800       0.005297  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  ,
            Date        Open        High         Low       Close   Adj Close  \
  490 2019-12-12  204.770004  207.320007  204.490005  206.509995  200.768051   
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  
         Volume  Daily Returns  
  490  32612000       0.007464  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  ,
            Date        Open        High         Low       Close   Adj Close  \
  491 2019-12-13  206.399994  207.910004  205.960007  207.190002  201.429153   
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  
         Volume  Daily Returns  
  491  32519400       0.003293  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  ,
            Date        Open        High         Low       Close   Adj Close  \
  492 2019-12-16  208.550003  209.529999  208.479996  209.270004  203.451340   
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  
         Volume  Daily Returns  
  492  21296600       0.010039  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  ,
            Date        Open        High         Low       Close   Adj Close  \
  493 2019-12-17  209.539993  209.710007  209.039993  209.389999  203.568024   
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  
         Volume  Daily Returns  
  493  15996100       0.000574  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  ,
            Date        Open        High         Low       Close   Adj Close  \
  494 2019-12-18  209.570007  210.130005  209.330002  209.550003  203.723541   
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  
         Volume  Daily Returns  
  494  15443300       0.000764  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  ,
            Date        Open        High         Low       Close   Adj Close  \
  495 2019-12-19  209.639999  210.929993  209.619995  210.860001  204.997131   
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  
         Volume  Daily Returns  
  495  17865900       0.006252  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  ,
            Date        Open        High         Low       Close   Adj Close  \
  496 2019-12-20  211.860001  212.520004  211.270004  211.710007  205.823532   
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  
         Volume  Daily Returns  
  496  27672600       0.004031  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  ,
            Date        Open        High         Low       Close   Adj Close  \
  497 2019-12-23  212.000000  212.149994  211.630005  211.809998  206.367172   
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  
         Volume  Daily Returns  
  497  23774700       0.002641  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  ,
            Date        Open        High         Low       Close   Adj Close  \
  498 2019-12-24  212.000000  212.089996  211.440002  211.919998  206.474365   
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  
         Volume  Daily Returns  
  498   7089000       0.000519  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  ,
            Date        Open        High         Low       Close   Adj Close  \
  499 2019-12-26  212.259995  213.809998  212.229996  213.789993  208.296295   
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  
         Volume  Daily Returns  
  499  17067500       0.008824  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  ,
            Date        Open        High         Low       Close   Adj Close  \
  500 2019-12-27  214.539993  214.559998  213.039993  213.610001  208.120941   
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  
         Volume  Daily Returns  
  500  18134100      -0.000842  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  ,
            Date        Open        High         Low       Close   Adj Close  \
  501 2019-12-30  213.500000  213.630005  211.160004  212.210007  206.756897   
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  
         Volume  Daily Returns  
  501  21815500      -0.006554  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  ,
            Date        Open        High         Low       Close   Adj Close  \
  502 2019-12-31  211.529999  212.759995  211.199997  212.610001  207.146591   
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  
         Volume  Daily Returns  
  502  18170900       0.001885  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  ,
            Date        Open        High         Low       Close   Adj Close  \
  503 2020-01-02  214.399994  216.160004  213.979996  216.160004  210.605362   
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  
         Volume  Daily Returns  
  503  30969400       0.016697  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  ,
            Date        Open        High         Low       Close   Adj Close  \
  504 2020-01-03  213.300003  215.470001  213.279999  214.179993  208.676254   
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  
         Volume  Daily Returns  
  504  27518900      -0.009160  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  ,
            Date        Open        High         Low       Close   Adj Close  \
  505 2020-01-06  212.500000  215.589996  212.240005  215.559998  210.020798   
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  
         Volume  Daily Returns  
  505  21655300       0.006443  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  ,
            Date        Open        High         Low       Close   Adj Close  \
  506 2020-01-07  215.639999  216.139999  214.850006  215.529999  209.991562   
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  
         Volume  Daily Returns  
  506  22139300      -0.000139  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  ,
            Date        Open        High         Low       Close   Adj Close  \
  507 2020-01-08  215.500000  218.139999  215.160004  217.149994  211.569931   
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  
         Volume  Daily Returns  
  507  26397300       0.007516  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  ,
            Date        Open        High         Low       Close   Adj Close  \
  508 2020-01-09  218.940002  219.410004  217.710007  218.990005  213.362671   
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  
         Volume  Daily Returns  
  508  23547000       0.008474  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  ,
            Date        Open        High         Low       Close   Adj Close  \
  509 2020-01-10  219.850006  219.869995  218.039993  218.429993  212.817047   
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  
         Volume  Daily Returns  
  509  21898500      -0.002557  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  ,
            Date        Open        High         Low       Close   Adj Close  \
  510 2020-01-13  219.330002  220.979996  218.979996  220.949997  215.272293   
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  
         Volume  Daily Returns  
  510  22756900       0.011537  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  
  539  97743000      -0.027192  ,
            Date        Open        High         Low       Close   Adj Close  \
  511 2020-01-14  220.839996  221.210007  219.740005  220.080002  214.424652   
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  
         Volume  Daily Returns  
  511  24418100      -0.003938  
  512  25742100       0.000409  
  513  18805000       0.009584  
  514  24325200       0.004949  
  515  21146300      -0.000448  
  516  20736400       0.002642  
  517  26496100       0.003216  
  518  37436500      -0.008415  
  519  42264400      -0.020655  
  520  26731900       0.015360  
  521  28924500       0.001626  
  522  39568100       0.003562  
  523  52015800      -0.015858  
  524  25408600       0.015109  
  525  30691200       0.022889  
  526  38534800       0.003297  
  527  22467100       0.008632  
  528  25884900      -0.004301  
  529  21478900       0.012086  
  530  30198000       0.000172  
  531  24471300       0.009741  
  532  22773200      -0.001281  
  533  23438500       0.002864  
  534  24394500       0.000383  
  535  22230500       0.009585  
  536  42604000      -0.009283  
  537  66017200      -0.019210  
  538  84522600      -0.038563  
  539  97743000      -0.027192  
  540  79537700       0.005154  ,
            Date        Open        High         Low       Close   Adj Close  \
  512 2020-01-15  220.199997  221.199997  219.449997  220.169998  214.512329   
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  
          Volume  Daily Returns  
  512   25742100       0.000409  
  513   18805000       0.009584  
  514   24325200       0.004949  
  515   21146300      -0.000448  
  516   20736400       0.002642  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  ,
            Date        Open        High         Low       Close   Adj Close  \
  513 2020-01-16  221.270004  222.320007  220.800003  222.279999  216.568115   
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  
          Volume  Daily Returns  
  513   18805000       0.009584  
  514   24325200       0.004949  
  515   21146300      -0.000448  
  516   20736400       0.002642  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  ,
            Date        Open        High         Low       Close   Adj Close  \
  514 2020-01-17  223.279999  223.559998  222.119995  223.380005  217.639862   
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  
          Volume  Daily Returns  
  514   24325200       0.004949  
  515   21146300      -0.000448  
  516   20736400       0.002642  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  ,
            Date        Open        High         Low       Close   Adj Close  \
  515 2020-01-21  222.759995  223.839996  222.660004  223.279999  217.542419   
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  
          Volume  Daily Returns  
  515   21146300      -0.000448  
  516   20736400       0.002642  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  ,
            Date        Open        High         Low       Close   Adj Close  \
  516 2020-01-22  224.410004  225.149994  223.589996  223.869995  218.117249   
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  
          Volume  Daily Returns  
  516   20736400       0.002642  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  ,
            Date        Open        High         Low       Close   Adj Close  \
  517 2020-01-23  223.740005  224.690002  222.699997  224.589996  218.818756   
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  
          Volume  Daily Returns  
  517   26496100       0.003216  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  ,
            Date        Open        High         Low       Close   Adj Close  \
  518 2020-01-24  225.639999  225.880005  221.669998  222.699997  216.977310   
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  
          Volume  Daily Returns  
  518   37436500      -0.008415  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  ,
            Date        Open        High         Low       Close   Adj Close  \
  519 2020-01-27  217.669998  219.279999  217.179993  218.100006  212.495544   
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  
          Volume  Daily Returns  
  519   42264400      -0.020655  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  ,
            Date        Open        High         Low       Close   Adj Close  \
  520 2020-01-28  219.639999  221.960007  219.059998  221.449997  215.759430   
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  
          Volume  Daily Returns  
  520   26731900       0.015360  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  ,
            Date        Open        High         Low       Close   Adj Close  \
  521 2020-01-29  222.679993  222.929993  220.830002  221.809998  216.110199   
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  
          Volume  Daily Returns  
  521   28924500       0.001626  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  ,
            Date        Open        High         Low       Close   Adj Close  \
  522 2020-01-30  220.380005  222.699997  219.690002  222.600006  216.879883   
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  
          Volume  Daily Returns  
  522   39568100       0.003562  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  ,
            Date        Open        High         Low       Close   Adj Close  \
  523 2020-01-31  223.529999  223.559998  218.289993  219.070007  213.440598   
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  
          Volume  Daily Returns  
  523   52015800      -0.015858  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  ,
            Date        Open        High         Low       Close   Adj Close  \
  524 2020-02-03  220.139999  222.889999  219.990005  222.380005  216.665543   
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  
          Volume  Daily Returns  
  524   25408600       0.015109  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  ,
            Date        Open        High         Low       Close   Adj Close  \
  525 2020-02-04  225.419998  227.860001  224.649994  227.470001  221.624741   
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  
          Volume  Daily Returns  
  525   30691200       0.022889  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  ,
            Date        Open        High         Low       Close   Adj Close  \
  526 2020-02-05  230.210007  230.250000  226.850006  228.220001  222.355453   
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  
          Volume  Daily Returns  
  526   38534800       0.003297  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  ,
            Date        Open        High         Low       Close   Adj Close  \
  527 2020-02-06  228.789993  230.250000  227.979996  230.190002  224.274872   
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  
          Volume  Daily Returns  
  527   22467100       0.008632  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  ,
            Date        Open        High         Low       Close   Adj Close  \
  528 2020-02-07  229.160004  230.440002  228.539993  229.199997  223.310272   
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  
          Volume  Daily Returns  
  528   25884900      -0.004301  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  ,
            Date        Open        High         Low       Close   Adj Close  \
  529 2020-02-10  228.440002  231.979996  228.380005  231.970001  226.009094   
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  
          Volume  Daily Returns  
  529   21478900       0.012086  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  ,
            Date        Open        High         Low       Close   Adj Close  \
  530 2020-02-11  233.250000  234.020004  231.399994  232.009995  226.048065   
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  
          Volume  Daily Returns  
  530   30198000       0.000172  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  ,
            Date        Open        High         Low       Close   Adj Close  \
  531 2020-02-12  233.380005  234.380005  232.800003  234.270004  228.250031   
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  
          Volume  Daily Returns  
  531   24471300       0.009741  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  ,
            Date        Open        High         Low       Close   Adj Close  \
  532 2020-02-13  232.639999  234.929993  232.360001  233.970001  227.957718   
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  
          Volume  Daily Returns  
  532   22773200      -0.001281  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  ,
            Date        Open        High         Low       Close   Adj Close  \
  533 2020-02-14  234.339996  234.860001  233.550003  234.639999  228.610519   
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  
          Volume  Daily Returns  
  533   23438500       0.002864  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  ,
            Date        Open        High         Low       Close   Adj Close  \
  534 2020-02-18  233.500000  235.169998  233.250000  234.729996  228.698181   
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  
          Volume  Daily Returns  
  534   24394500       0.000383  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  ,
            Date        Open        High         Low       Close   Adj Close  \
  535 2020-02-19  236.130005  237.470001  235.850006  236.979996  230.890350   
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  
          Volume  Daily Returns  
  535   22230500       0.009585  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  ,
            Date        Open        High         Low       Close   Adj Close  \
  536 2020-02-20  236.460007  236.949997  231.880005  234.779999  228.746902   
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  
          Volume  Daily Returns  
  536   42604000      -0.009283  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  ,
            Date        Open        High         Low       Close   Adj Close  \
  537 2020-02-21  233.610001  234.009995  229.320007  230.270004  224.352783   
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  
          Volume  Daily Returns  
  537   66017200      -0.019210  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  ,
            Date        Open        High         Low       Close   Adj Close  \
  538 2020-02-24  221.679993  224.250000  220.259995  221.389999  215.701019   
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  
          Volume  Daily Returns  
  538   84522600      -0.038563  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  ,
            Date        Open        High         Low       Close   Adj Close  \
  539 2020-02-25  223.250000  223.990005  214.740005  215.369995  209.835693   
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  
          Volume  Daily Returns  
  539   97743000      -0.027192  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  ,
            Date        Open        High         Low       Close   Adj Close  \
  540 2020-02-26  216.710007  220.279999  214.899994  216.479996  210.917130   
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  
          Volume  Daily Returns  
  540   79537700       0.005154  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  ,
            Date        Open        High         Low       Close   Adj Close  \
  541 2020-02-27  210.899994  216.419998  205.500000  205.639999  200.355713   
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  
          Volume  Daily Returns  
  541  121822600      -0.050074  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  ,
            Date        Open        High         Low       Close   Adj Close  \
  542 2020-02-28  198.639999  207.169998  198.169998  205.800003  200.511581   
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  
          Volume  Daily Returns  
  542  148173700       0.000778  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  ,
            Date        Open        High         Low       Close   Adj Close  \
  543 2020-03-02  208.880005  216.570007  205.940002  216.419998  210.858673   
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  
          Volume  Daily Returns  
  543  112933900       0.051603  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  ,
            Date        Open        High         Low       Close   Adj Close  \
  544 2020-03-03  217.110001  219.610001  207.619995  209.479996  204.097015   
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  
          Volume  Daily Returns  
  544  131953500      -0.032067  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  ,
            Date        Open        High         Low       Close   Adj Close  \
  545 2020-03-04  213.320007  218.330002  211.369995  218.220001  212.612427   
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  
          Volume  Daily Returns  
  545   73086200       0.041722  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  ,
            Date        Open        High         Low       Close   Adj Close  \
  546 2020-03-05  212.690002  216.360001  210.100006  211.589996  206.152817   
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  
          Volume  Daily Returns  
  546   78705500      -0.030382  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  ,
            Date        Open        High         Low       Close   Adj Close  \
  547 2020-03-06  204.669998  209.149994  202.910004  208.020004  202.674530   
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  
          Volume  Daily Returns  
  547   89828400      -0.016872  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  ,
            Date        Open        High         Low       Close   Adj Close  \
  548 2020-03-09  193.479996  201.160004  192.110001  193.570007  188.595871   
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  
          Volume  Daily Returns  
  548  116424000      -0.069464  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  ,
            Date        Open        High         Low       Close   Adj Close  \
  549 2020-03-10  201.110001  204.300003  193.679993  204.110001  198.865051   
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  
          Volume  Daily Returns  
  549  100599200       0.054451  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  ,
            Date        Open        High         Low       Close   Adj Close  \
  550 2020-03-11  199.350006  200.750000  192.729996  195.220001  190.203491   
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  
          Volume  Daily Returns  
  550   89168800      -0.043555  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  ,
            Date        Open        High         Low       Close   Adj Close  \
  551 2020-03-12  182.089996  190.779999  176.940002  177.320007  172.763428   
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  
          Volume  Daily Returns  
  551  137820700      -0.091692  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  ,
            Date        Open        High         Low       Close   Adj Close  \
  552 2020-03-13  187.070007  194.479996  178.130005  192.339996  187.397446   
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  
          Volume  Daily Returns  
  552  134882000       0.084706  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  ,
            Date        Open        High         Low       Close   Adj Close  \
  553 2020-03-16  174.149994  184.679993  169.160004  169.300003  164.949539   
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  
          Volume  Daily Returns  
  553   92054400      -0.119788  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  ,
            Date        Open        High         Low       Close   Adj Close  \
  554 2020-03-17  175.470001  184.389999  169.779999  182.139999  177.459579   
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  
          Volume  Daily Returns  
  554  121257100       0.075842  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  
  583   46862800      -0.018835  ,
            Date        Open        High         Low       Close   Adj Close  \
  555 2020-03-18  171.610001  179.220001  166.800003  176.600006  172.061966   
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  
          Volume  Daily Returns  
  555  114156300      -0.030416  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  
  583   46862800      -0.018835  
  584   48716400       0.035461  ,
            Date        Open        High         Low       Close   Adj Close  \
  556 2020-03-19  175.690002  183.490005  171.630005  177.660004  173.094727   
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  
          Volume  Daily Returns  
  556  120896500       0.006002  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  
  583   46862800      -0.018835  
  584   48716400       0.035461  
  585   43359500      -0.000411  ,
            Date        Open        High         Low       Close   Adj Close  \
  557 2020-03-20  181.740005  182.869995  170.100006  170.699997  166.313538   
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  
          Volume  Daily Returns  
  557  118983900      -0.039176  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  
  583   46862800      -0.018835  
  584   48716400       0.035461  
  585   43359500      -0.000411  
  586   48795000      -0.028185  ,
            Date        Open        High         Low       Close   Adj Close  \
  558 2020-03-23  170.919998  174.210007  164.929993  170.460007  166.433670   
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  
          Volume  Daily Returns  
  558  124639800       0.000722  
  559   94881800       0.077437  
  560   88754900      -0.007405  
  561   79887600       0.052661  
  562   58845000      -0.034393  
  563   49356900       0.036374  
  564   62659300      -0.008540  
  565   53715400      -0.042490  
  566   56465300       0.020295  
  567   47487600      -0.014193  
  568   64763500       0.071495  
  569   69904500      -0.000407  
  570   45940400       0.021232  
  571   68252600       0.001446  
  572   42853900       0.010803  
  573   63959600       0.043491  
  574   47036000      -0.011470  
  575   64657400       0.018240  
  576   62863200       0.009566  
  577   38249100      -0.011844  
  578   72932800      -0.036900  
  579   40089100       0.029675  
  580   43278500      -0.002133  
  581   34231900       0.015770  
  582   36451700       0.008043  
  583   46862800      -0.018835  
  584   48716400       0.035461  
  585   43359500      -0.000411  
  586   48795000      -0.028185  
  587   32841000       0.011657  ,
            Date        Open        High         Low       Close   Adj Close  \
  559 2020-03-24  179.910004  183.830002  177.949997  183.660004  179.321854   
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  
         Volume  Daily Returns  
  559  94881800       0.077437  
  560  88754900      -0.007405  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  ,
            Date        Open        High         Low       Close   Adj Close  \
  560 2020-03-25  184.419998  189.509995  179.979996  182.300003  177.993958   
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  
         Volume  Daily Returns  
  560  88754900      -0.007405  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  ,
            Date        Open        High         Low       Close   Adj Close  \
  561 2020-03-26  183.869995  192.720001  183.610001  191.899994  187.367218   
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  
         Volume  Daily Returns  
  561  79887600       0.052661  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  ,
            Date        Open        High         Low       Close   Adj Close  \
  562 2020-03-27  186.929993  190.509995  184.660004  185.300003  180.923141   
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  
         Volume  Daily Returns  
  562  58845000      -0.034393  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  ,
            Date        Open        High         Low       Close   Adj Close  \
  563 2020-03-30  187.059998  192.490005  186.339996  192.039993  187.503952   
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  
         Volume  Daily Returns  
  563  49356900       0.036374  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  ,
            Date        Open        High         Low       Close   Adj Close  \
  564 2020-03-31  191.720001  195.250000  189.199997  190.399994  185.902649   
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  
         Volume  Daily Returns  
  564  62659300      -0.008540  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  ,
            Date        Open        High         Low       Close   Adj Close  \
  565 2020-04-01  184.770004  187.660004  180.860001  182.309998  178.003723   
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  
         Volume  Daily Returns  
  565  53715400      -0.042490  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  ,
            Date        Open        High         Low       Close   Adj Close  \
  566 2020-04-02  181.240005  190.100006  180.970001  186.009995  181.616333   
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  
         Volume  Daily Returns  
  566  56465300       0.020295  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  ,
            Date        Open        High         Low       Close   Adj Close  \
  567 2020-04-03  185.550003  187.070007  181.289993  183.369995  179.038696   
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  
         Volume  Daily Returns  
  567  47487600      -0.014193  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  ,
            Date        Open        High         Low       Close   Adj Close  \
  568 2020-04-06  190.479996  197.649994  189.190002  196.479996  191.839020   
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  
         Volume  Daily Returns  
  568  64763500       0.071495  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  ,
            Date        Open        High         Low       Close   Adj Close  \
  569 2020-04-07  202.369995  202.660004  196.000000  196.399994  191.760941   
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  
         Volume  Daily Returns  
  569  69904500      -0.000407  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  ,
            Date        Open        High         Low       Close   Adj Close  \
  570 2020-04-08  198.149994  201.169998  196.169998  200.570007  195.832428   
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  
         Volume  Daily Returns  
  570  45940400       0.021232  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  ,
            Date        Open        High         Low       Close   Adj Close  \
  571 2020-04-09  202.350006  203.220001  199.029999  200.860001  196.115570   
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  
         Volume  Daily Returns  
  571  68252600       0.001446  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  ,
            Date        Open        High         Low       Close   Adj Close  \
  572 2020-04-13  200.000000  203.419998  198.750000  203.029999  198.234299   
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  
         Volume  Daily Returns  
  572  42853900       0.010803  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  ,
            Date        Open        High         Low       Close   Adj Close  \
  573 2020-04-14  207.229996  212.500000  206.419998  211.860001  206.855774   
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  
         Volume  Daily Returns  
  573  63959600       0.043491  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  ,
            Date        Open        High         Low       Close   Adj Close  \
  574 2020-04-15  208.479996  211.830002  207.119995  209.429993  204.483154   
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  
         Volume  Daily Returns  
  574  47036000      -0.011470  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  ,
            Date        Open        High         Low       Close   Adj Close  \
  575 2020-04-16  211.690002  214.369995  209.690002  213.250000  208.212952   
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  
         Volume  Daily Returns  
  575  64657400       0.018240  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  ,
            Date        Open        High         Low       Close   Adj Close  \
  576 2020-04-17  216.169998  216.509995  212.080002  215.289993  210.204727   
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  
         Volume  Daily Returns  
  576  62863200       0.009566  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  ,
            Date        Open        High         Low       Close   Adj Close  \
  577 2020-04-20  213.360001  215.880005  212.570007  212.740005  207.714966   
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  
         Volume  Daily Returns  
  577  38249100      -0.011844  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  ,
            Date        Open        High         Low       Close   Adj Close  \
  578 2020-04-21  210.600006  211.160004  203.630005  204.889999  200.050369   
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  
         Volume  Daily Returns  
  578  72932800      -0.036900  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  ,
            Date        Open        High         Low       Close   Adj Close  \
  579 2020-04-22  209.100006  212.350006  208.330002  210.970001  205.986801   
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  
         Volume  Daily Returns  
  579  40089100       0.029675  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  ,
            Date        Open        High         Low       Close   Adj Close  \
  580 2020-04-23  211.789993  214.440002  210.100006  210.520004  205.547440   
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  
         Volume  Daily Returns  
  580  43278500      -0.002133  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  ,
            Date        Open        High         Low       Close   Adj Close  \
  581 2020-04-24  210.970001  214.300003  209.500000  213.839996  208.789001   
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  
         Volume  Daily Returns  
  581  34231900       0.015770  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  ,
            Date        Open        High         Low       Close   Adj Close  \
  582 2020-04-27  216.190002  216.630005  214.500000  215.559998  210.468384   
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  
         Volume  Daily Returns  
  582  36451700       0.008043  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  ,
            Date        Open        High         Low       Close   Adj Close  \
  583 2020-04-28  217.320007  217.320007  211.210007  211.500000  206.504242   
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  
         Volume  Daily Returns  
  583  46862800      -0.018835  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  ,
            Date        Open        High         Low       Close   Adj Close  \
  584 2020-04-29  216.190002  219.970001  215.139999  219.000000  213.827133   
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  
         Volume  Daily Returns  
  584  48716400       0.035461  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  ,
            Date        Open        High         Low       Close   Adj Close  \
  585 2020-04-30  219.949997  220.039993  217.350006  218.910004  213.739227   
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  
         Volume  Daily Returns  
  585  43359500      -0.000411  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  ,
            Date        Open        High         Low       Close   Adj Close  \
  586 2020-05-01  214.500000  216.669998  211.679993  212.740005  207.714966   
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  
         Volume  Daily Returns  
  586  48795000      -0.028185  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  ,
            Date        Open        High         Low       Close   Adj Close  \
  587 2020-05-04  211.460007  215.449997  211.119995  215.220001  210.136398   
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  
         Volume  Daily Returns  
  587  32841000       0.011657  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  ,
            Date        Open        High         Low       Close   Adj Close  \
  588 2020-05-05  217.440002  220.139999  216.850006  217.660004  212.518768   
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  
         Volume  Daily Returns  
  588  37783100       0.011337  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  ,
            Date        Open        High         Low       Close   Adj Close  \
  589 2020-05-06  219.399994  221.039993  218.110001  219.000000  213.827133   
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  
         Volume  Daily Returns  
  589  36455200       0.006156  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  ,
            Date        Open        High         Low       Close   Adj Close  \
  590 2020-05-07  221.820007  222.729996  220.419998  221.820007  216.580521   
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  
         Volume  Daily Returns  
  590  38624800       0.012877  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  ,
            Date        Open        High         Low       Close   Adj Close  \
  591 2020-05-08  223.550003  225.000000  222.479996  224.860001  219.548691   
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  
         Volume  Daily Returns  
  591  31852300       0.013705  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  ,
            Date        Open        High         Low       Close   Adj Close  \
  592 2020-05-11  223.490005  227.929993  223.250000  226.869995  221.511200   
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  
         Volume  Daily Returns  
  592  35714100       0.008939  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  ,
            Date        Open        High         Low       Close   Adj Close  \
  593 2020-05-12  227.490005  228.100006  222.089996  222.119995  216.873428   
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  
         Volume  Daily Returns  
  593  41054100      -0.020937  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  ,
            Date        Open        High         Low       Close   Adj Close  \
  594 2020-05-13  222.660004  224.610001  216.710007  219.339996  214.159073   
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  
         Volume  Daily Returns  
  594  65521200      -0.012516  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  ,
            Date        Open        High         Low       Close   Adj Close  \
  595 2020-05-14  217.970001  221.869995  215.990005  221.830002  216.590240   
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  
         Volume  Daily Returns  
  595  51549300       0.011352  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  ,
            Date        Open        High         Low       Close   Adj Close  \
  596 2020-05-15  218.779999  223.330002  218.330002  223.270004  217.996246   
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  
         Volume  Daily Returns  
  596  55747200       0.006492  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  ,
            Date        Open        High         Low       Close   Adj Close  \
  597 2020-05-18  226.279999  228.679993  225.470001  227.429993  222.057983   
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  
         Volume  Daily Returns  
  597  42398100       0.018632  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  ,
            Date        Open        High         Low       Close   Adj Close  \
  598 2020-05-19  227.699997  229.850006  226.710007  226.860001  221.501480   
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  
         Volume  Daily Returns  
  598  36237300      -0.002506  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  ,
            Date        Open        High         Low       Close   Adj Close  \
  599 2020-05-20  229.500000  231.759995  229.479996  231.389999  225.924438   
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  
         Volume  Daily Returns  
  599  37417000       0.019968  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  ,
            Date        Open        High         Low       Close   Adj Close  \
  600 2020-05-21  231.440002  232.139999  228.339996  228.869995  223.463974   
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  
         Volume  Daily Returns  
  600  43642900      -0.010891  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  ,
            Date        Open        High         Low       Close   Adj Close  \
  601 2020-05-22  228.449997  229.869995  227.500000  229.660004  224.235321   
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  
         Volume  Daily Returns  
  601  28762400       0.003452  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  ,
            Date        Open        High         Low       Close   Adj Close  \
  602 2020-05-26  233.360001  233.570007  228.789993  229.039993  223.629929   
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  
         Volume  Daily Returns  
  602  33055300      -0.002700  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  ,
            Date        Open        High         Low       Close   Adj Close  \
  603 2020-05-27  228.690002  230.410004  223.940002  230.289993  224.850418   
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  
         Volume  Daily Returns  
  603  55665600       0.005458  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  ,
            Date        Open        High         Low       Close   Adj Close  \
  604 2020-05-28  229.110001  233.470001  229.050003  229.990005  224.557526   
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  
         Volume  Daily Returns  
  604  42784300      -0.001303  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  ,
            Date        Open        High         Low       Close   Adj Close  \
  605 2020-05-29  230.380005  233.600006  228.759995  233.360001  227.847900   
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  
         Volume  Daily Returns  
  605  50691800       0.014653  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  ,
            Date        Open        High         Low       Close   Adj Close  \
  606 2020-06-01  232.460007  234.449997  232.000000  234.059998  228.531387   
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  
         Volume  Daily Returns  
  606  25776000       0.003000  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  ,
            Date        Open        High         Low       Close   Adj Close  \
  607 2020-06-02  234.500000  235.690002  232.009995  235.630005  230.064316   
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  
         Volume  Daily Returns  
  607  33383400       0.006708  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  ,
            Date        Open        High         Low       Close   Adj Close  \
  608 2020-06-03  236.259995  237.470001  235.350006  236.690002  231.099243   
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  
         Volume  Daily Returns  
  608  37228700       0.004498  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  ,
            Date        Open        High         Low       Close   Adj Close  \
  609 2020-06-04  236.330002  237.789993  233.679993  235.029999  229.478455   
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  
         Volume  Daily Returns  
  609  38716100      -0.007013  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  ,
            Date        Open        High         Low       Close   Adj Close  \
  610 2020-06-05  236.220001  240.300003  235.630005  239.690002  234.028412   
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  
         Volume  Daily Returns  
  610  47365600       0.019827  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  ,
            Date        Open        High         Low       Close   Adj Close  \
  611 2020-06-08  239.539993  241.679993  237.910004  241.550003  235.844482   
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  
         Volume  Daily Returns  
  611  32937300       0.007760  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  ,
            Date        Open        High         Low       Close   Adj Close  \
  612 2020-06-09  240.660004  244.179993  240.470001  243.300003  237.553085   
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  
         Volume  Daily Returns  
  612  35046300       0.007245  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  ,
            Date        Open        High         Low       Close   Adj Close  \
  613 2020-06-10  245.050003  247.820007  244.509995  246.220001  240.404144   
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  
         Volume  Daily Returns  
  613  58084400       0.012002  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  ,
            Date        Open        High         Low       Close   Adj Close  \
  614 2020-06-11  242.160004  243.589996  233.960007  234.020004  228.492355   
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  
         Volume  Daily Returns  
  614  72919400      -0.049549  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  ,
            Date        Open        High         Low       Close   Adj Close  \
  615 2020-06-12  239.089996  240.399994  231.740005  235.880005  230.308411   
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  
         Volume  Daily Returns  
  615  72034800       0.007948  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  ,
            Date        Open        High         Low       Close   Adj Close  \
  616 2020-06-15  232.440002  239.449997  231.470001  238.750000  233.110596   
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  
         Volume  Daily Returns  
  616  45307400       0.012167  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  ,
            Date        Open        High         Low       Close   Adj Close  \
  617 2020-06-16  243.779999  244.389999  239.100006  242.850006  237.113754   
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  
         Volume  Daily Returns  
  617  48890100       0.017173  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  ,
            Date        Open        High         Low       Close   Adj Close  \
  618 2020-06-17  244.399994  245.500000  242.729996  243.619995  237.865570   
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  
         Volume  Daily Returns  
  618  34749300       0.003171  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  ,
            Date        Open        High         Low       Close   Adj Close  \
  619 2020-06-18  243.289993  244.529999  242.490005  244.279999  238.509979   
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  
         Volume  Daily Returns  
  619  30578600       0.002709  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  ,
            Date        Open        High         Low       Close   Adj Close  \
  620 2020-06-19  246.729996  247.000000  242.449997  244.240005  238.470917   
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  
         Volume  Daily Returns  
  620  49422100      -0.000164  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  ,
            Date        Open        High         Low       Close   Adj Close  \
  621 2020-06-22  243.679993  246.869995  243.380005  246.740005  241.330856   
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  
         Volume  Daily Returns  
  621  24068700       0.011993  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  ,
            Date        Open        High         Low       Close   Adj Close  \
  622 2020-06-23  248.389999  251.149994  247.820007  248.839996  243.384796   
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  
         Volume  Daily Returns  
  622  32767400       0.008511  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  ,
            Date        Open        High         Low       Close   Adj Close  \
  623 2020-06-24  248.059998  249.330002  242.160004  243.710007  238.367249   
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  
         Volume  Daily Returns  
  623  46032400      -0.020616  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  ,
            Date        Open        High         Low       Close   Adj Close  \
  624 2020-06-25  243.800003  246.339996  241.139999  246.029999  240.636383   
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  
         Volume  Daily Returns  
  624  36940800       0.009519  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  ,
            Date        Open        High         Low       Close   Adj Close  \
  625 2020-06-26  245.779999  245.960007  239.679993  240.220001  234.953781   
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  
         Volume  Daily Returns  
  625  52824600      -0.023615  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  ,
            Date        Open        High         Low       Close   Adj Close  \
  626 2020-06-29  239.970001  242.850006  237.350006  242.839996  237.516342   
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  
         Volume  Daily Returns  
  626  34377800       0.010907  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  ,
            Date        Open        High         Low       Close   Adj Close  \
  627 2020-06-30  242.770004  248.160004  242.580002  247.600006  242.171997   
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  
         Volume  Daily Returns  
  627  38909200       0.019601  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  ,
            Date        Open        High         Low       Close   Adj Close  \
  628 2020-07-01  247.639999  251.520004  247.080002  250.490005  244.998627   
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  
         Volume  Daily Returns  
  628  34689200       0.011672  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  ,
            Date        Open        High         Low       Close   Adj Close  \
  629 2020-07-02  253.020004  254.270004  251.710007  252.190002  246.661362   
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  
         Volume  Daily Returns  
  629  31956500       0.006787  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  ,
            Date        Open        High         Low       Close   Adj Close  \
  630 2020-07-06  255.449997  258.929993  255.429993  258.390015  252.725449   
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  
         Volume  Daily Returns  
  630  34589000       0.024585  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  ,
            Date        Open        High         Low       Close   Adj Close  \
  631 2020-07-07  258.130005  260.880005  256.299988  256.609985  250.984451   
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  
         Volume  Daily Returns  
  631  36578200      -0.006889  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  ,
            Date        Open        High         Low       Close   Adj Close  \
  632 2020-07-08  257.980011  260.019989  256.500000  259.989990  254.290329   
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  
         Volume  Daily Returns  
  632  30426300       0.013172  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  ,
            Date        Open        High         Low       Close   Adj Close  \
  633 2020-07-09  261.970001  262.869995  257.630005  262.179993  256.432281   
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  
         Volume  Daily Returns  
  633  40312900       0.008423  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  ,
            Date        Open        High         Low       Close   Adj Close  \
  634 2020-07-10  262.029999  264.230011  259.260010  263.970001  258.183105   
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  
         Volume  Daily Returns  
  634  32885300       0.006828  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  ,
            Date        Open        High         Low       Close   Adj Close  \
  635 2020-07-13  266.910004  269.790009  257.690002  258.540009  252.872131   
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  
         Volume  Daily Returns  
  635  64108100      -0.020571  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  ,
            Date        Open        High         Low       Close   Adj Close  \
  636 2020-07-14  255.929993  260.790009  252.759995  260.369995  254.662033   
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  
         Volume  Daily Returns  
  636  72230500       0.007078  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  ,
            Date        Open        High         Low       Close   Adj Close  \
  637 2020-07-15  261.829987  262.690002  257.489990  260.899994  255.180374   
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  
         Volume  Daily Returns  
  637  54523900       0.002035  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  ,
            Date        Open        High         Low       Close   Adj Close  \
  638 2020-07-16  258.019989  259.779999  255.619995  259.119995  253.439407   
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  
         Volume  Daily Returns  
  638  47594100      -0.006822  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  ,
            Date        Open        High         Low       Close   Adj Close  \
  639 2020-07-17  259.589996  260.309998  257.170013  259.420013  253.732864   
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  
         Volume  Daily Returns  
  639  35137900       0.001158  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  ,
            Date        Open        High         Low       Close   Adj Close  \
  640 2020-07-20  260.079987  267.429993  258.790009  266.779999  260.931580   
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  
         Volume  Daily Returns  
  640  40610100       0.028371  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  ,
            Date        Open        High         Low       Close   Adj Close  \
  641 2020-07-21  268.399994  268.410004  263.130005  264.000000  258.212402   
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  
         Volume  Daily Returns  
  641  43243800      -0.010421  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  ,
            Date        Open        High         Low       Close   Adj Close  \
  642 2020-07-22  264.510010  265.890015  262.549988  264.929993  259.122070   
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  
         Volume  Daily Returns  
  642  29865500       0.003523  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  
  671  36216200       0.017092  ,
            Date        Open        High         Low       Close   Adj Close  \
  643 2020-07-23  264.510010  265.239990  256.549988  258.010010  252.353790   
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  
         Volume  Daily Returns  
  643  51363500      -0.026120  
  644  54054500      -0.009496  
  645  36445700       0.017843  
  646  31302400      -0.012725  
  647  27556900       0.011526  
  648  41774500       0.005235  
  649  53686300       0.017845  
  650  32081600       0.013507  
  651  24911300       0.003712  
  652  21612100       0.002478  
  653  28048200       0.013245  
  654  44969400      -0.011542  
  655  35088400      -0.004273  
  656  43104300      -0.018941  
  657  38773400       0.025152  
  658  31895700       0.002281  
  659  30799500      -0.001174  
  660  24803000       0.011611  
  661  23529500       0.009625  
  662  31999400      -0.006728  
  663  27723400       0.013871  
  664  34748900       0.006930  
  665  36418500       0.006244  
  666  34866600       0.007862  
  667  42216700       0.021339  
  668  49482700      -0.003117  
  669  28021000       0.005085  
  670  36321000       0.008033  
  671  36216200       0.017092  
  672  50836800       0.009469  ,
            Date        Open        High         Low       Close   Adj Close  \
  644 2020-07-24  254.039993  256.929993  251.320007  255.559998  249.957443   
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  
          Volume  Daily Returns  
  644   54054500      -0.009496  
  645   36445700       0.017843  
  646   31302400      -0.012725  
  647   27556900       0.011526  
  648   41774500       0.005235  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  ,
            Date        Open        High         Low       Close   Adj Close  \
  645 2020-07-27  257.260010  260.519989  256.450012  260.119995  254.417496   
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  
          Volume  Daily Returns  
  645   36445700       0.017843  
  646   31302400      -0.012725  
  647   27556900       0.011526  
  648   41774500       0.005235  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  ,
            Date        Open        High         Low       Close   Adj Close  \
  646 2020-07-28  259.309998  259.850006  256.510010  256.809998  251.180069   
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  
          Volume  Daily Returns  
  646   31302400      -0.012725  
  647   27556900       0.011526  
  648   41774500       0.005235  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  ,
            Date        Open        High         Low       Close   Adj Close  \
  647 2020-07-29  258.399994  260.660004  257.910004  259.769989  254.075180   
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  
          Volume  Daily Returns  
  647   27556900       0.011526  
  648   41774500       0.005235  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  ,
            Date        Open        High         Low       Close   Adj Close  \
  648 2020-07-30  257.739990  261.709991  256.549988  261.130005  255.405380   
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  
          Volume  Daily Returns  
  648   41774500       0.005235  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  ,
            Date        Open        High         Low       Close   Adj Close  \
  649 2020-07-31  265.910004  265.950012  260.850006  265.790009  259.963196   
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  
          Volume  Daily Returns  
  649   53686300       0.017845  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  ,
            Date        Open        High         Low       Close   Adj Close  \
  650 2020-08-03  268.000000  270.149994  267.869995  269.380005  263.474487   
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  
          Volume  Daily Returns  
  650   32081600       0.013507  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  ,
            Date        Open        High         Low       Close   Adj Close  \
  651 2020-08-04  268.859985  270.480011  268.089996  270.380005  264.452576   
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  
          Volume  Daily Returns  
  651   24911300       0.003712  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  ,
            Date        Open        High         Low       Close   Adj Close  \
  652 2020-08-05  270.880005  271.519989  269.959991  271.049988  265.107819   
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  
          Volume  Daily Returns  
  652   21612100       0.002478  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  ,
            Date        Open        High         Low       Close   Adj Close  \
  653 2020-08-06  270.850006  274.980011  270.190002  274.640015  268.619202   
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  
          Volume  Daily Returns  
  653   28048200       0.013245  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  ,
            Date        Open        High         Low       Close   Adj Close  \
  654 2020-08-07  274.079987  274.880005  269.250000  271.470001  265.518707   
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  
          Volume  Daily Returns  
  654   44969400      -0.011542  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  ,
            Date        Open        High         Low       Close   Adj Close  \
  655 2020-08-10  271.769989  271.980011  266.670013  270.309998  264.384094   
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  
          Volume  Daily Returns  
  655   35088400      -0.004273  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  ,
            Date        Open        High         Low       Close   Adj Close  \
  656 2020-08-11  269.109985  270.440002  264.630005  265.190002  259.376343   
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  
          Volume  Daily Returns  
  656   43104300      -0.018941  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  ,
            Date        Open        High         Low       Close   Adj Close  \
  657 2020-08-12  267.420013  272.839996  267.369995  271.859985  265.900085   
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  
          Volume  Daily Returns  
  657   38773400       0.025152  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  ,
            Date        Open        High         Low       Close   Adj Close  \
  658 2020-08-13  272.660004  274.829987  271.510010  272.480011  266.506500   
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  
          Volume  Daily Returns  
  658   31895700       0.002281  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  ,
            Date        Open        High         Low       Close   Adj Close  \
  659 2020-08-14  273.119995  273.399994  270.720001  272.160004  266.193573   
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  
          Volume  Daily Returns  
  659   30799500      -0.001174  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  ,
            Date        Open        High         Low       Close   Adj Close  \
  660 2020-08-17  273.929993  275.839996  272.200012  275.320007  269.284302   
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  
          Volume  Daily Returns  
  660   24803000       0.011611  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  ,
            Date        Open        High         Low       Close   Adj Close  \
  661 2020-08-18  276.420013  278.459991  274.910004  277.970001  271.876251   
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  
          Volume  Daily Returns  
  661   23529500       0.009625  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  ,
            Date        Open        High         Low       Close   Adj Close  \
  662 2020-08-19  277.929993  279.019989  275.570007  276.100006  270.047180   
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  
          Volume  Daily Returns  
  662   31999400      -0.006728  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  ,
            Date        Open        High         Low       Close   Adj Close  \
  663 2020-08-20  275.279999  280.429993  274.859985  279.929993  273.793121   
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  
          Volume  Daily Returns  
  663   27723400       0.013871  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  ,
            Date        Open        High         Low       Close   Adj Close  \
  664 2020-08-21  280.130005  282.339996  279.459991  281.869995  275.690643   
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  
          Volume  Daily Returns  
  664   34748900       0.006930  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  ,
            Date        Open        High         Low       Close   Adj Close  \
  665 2020-08-24  285.250000  286.000000  281.269989  283.630005  277.412079   
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  
          Volume  Daily Returns  
  665   36418500       0.006244  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  ,
            Date        Open        High         Low       Close   Adj Close  \
  666 2020-08-25  282.829987  286.059998  282.369995  285.859985  279.593201   
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  
          Volume  Daily Returns  
  666   34866600       0.007862  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  ,
            Date        Open        High         Low       Close   Adj Close  \
  667 2020-08-26  287.149994  292.220001  285.829987  291.959991  285.559448   
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  
          Volume  Daily Returns  
  667   42216700       0.021339  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  ,
            Date        Open        High         Low       Close   Adj Close  \
  668 2020-08-27  292.970001  293.850006  288.709991  291.049988  284.669434   
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  
          Volume  Daily Returns  
  668   49482700      -0.003117  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  ,
            Date        Open        High         Low       Close   Adj Close  \
  669 2020-08-28  292.329987  293.179993  290.929993  292.529999  286.117004   
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  
          Volume  Daily Returns  
  669   28021000       0.005085  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  ,
            Date        Open        High         Low       Close   Adj Close  \
  670 2020-08-31  293.070007  296.750000  292.619995  294.880005  288.415466   
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  
          Volume  Daily Returns  
  670   36321000       0.008033  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  
  699   79370700       0.030870  ,
            Date        Open        High         Low       Close   Adj Close  \
  671 2020-09-01  297.619995  300.040009  295.790009  299.920013  293.345032   
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  
          Volume  Daily Returns  
  671   36216200       0.017092  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  
  699   79370700       0.030870  
  700   64240000      -0.000034  ,
            Date        Open        High         Low       Close   Adj Close  \
  672 2020-09-02  303.279999  303.500000  296.890015  302.760010  296.122742   
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  
          Volume  Daily Returns  
  672   50836800       0.009469  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  
  699   79370700       0.030870  
  700   64240000      -0.000034  
  701   36949100      -0.008353  ,
            Date        Open        High         Low       Close   Adj Close  \
  673 2020-09-03  298.100006  298.619995  284.410004  287.410004  281.109253   
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  
          Volume  Daily Returns  
  673  110083300      -0.050700  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  
  699   79370700       0.030870  
  700   64240000      -0.000034  
  701   36949100      -0.008353  
  702   42514200      -0.006711  ,
            Date        Open        High         Low       Close   Adj Close  \
  674 2020-09-04  285.559998  288.929993  271.799988  283.579987  277.363159   
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  
          Volume  Daily Returns  
  674  123959000      -0.013326  
  675   99568600      -0.048064  
  676   64837900       0.029376  
  677   69667500      -0.019937  
  678   71809000      -0.006940  
  679   38525200       0.017415  
  680   41849900       0.014174  
  681   42321000      -0.015947  
  682   81570800      -0.015622  
  683   86251100      -0.012762  
  684   57168600       0.002398  
  685   41128900       0.018579  
  686   48837300      -0.030534  
  687   70631700       0.004656  
  688   55242400       0.023249  
  689   58438300       0.020769  
  690   27050000      -0.004510  
  691   49380800       0.006849  
  692   50020200       0.015872  
  693   75497400      -0.028131  
  694   28184600       0.021326  
  695   49704200      -0.017847  
  696   27539700       0.017299  
  697   25443300       0.005323  
  698   30201100       0.015280  
  699   79370700       0.030870  
  700   64240000      -0.000034  
  701   36949100      -0.008353  
  702   42514200      -0.006711  
  703   40570700      -0.005481  ,
            Date        Open        High         Low       Close   Adj Close  \
  675 2020-09-08  272.220001  278.220001  269.660004  269.950012  264.032043   
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  
         Volume  Daily Returns  
  675  99568600      -0.048064  
  676  64837900       0.029376  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  ,
            Date        Open        High         Low       Close   Adj Close  \
  676 2020-09-09  275.640015  280.049988  273.000000  277.880005  271.788147   
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  
         Volume  Daily Returns  
  676  64837900       0.029376  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  ,
            Date        Open        High         Low       Close   Adj Close  \
  677 2020-09-10  280.940002  282.200012  270.559998  272.339996  266.369568   
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  
         Volume  Daily Returns  
  677  69667500      -0.019937  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  ,
            Date        Open        High         Low       Close   Adj Close  \
  678 2020-09-11  274.149994  275.220001  266.899994  270.450012  264.521088   
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  
         Volume  Daily Returns  
  678  71809000      -0.006940  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  ,
            Date        Open        High         Low       Close   Adj Close  \
  679 2020-09-14  274.359985  277.220001  272.959991  275.160004  269.127808   
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  
         Volume  Daily Returns  
  679  38525200       0.017415  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  ,
            Date        Open        High         Low       Close   Adj Close  \
  680 2020-09-15  279.029999  280.450012  275.130005  279.059998  272.942352   
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  
         Volume  Daily Returns  
  680  41849900       0.014174  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  ,
            Date        Open        High         Low       Close   Adj Close  \
  681 2020-09-16  279.880005  280.359985  274.250000  274.609985  268.589783   
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  
         Volume  Daily Returns  
  681  42321000      -0.015947  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  ,
            Date        Open        High         Low       Close   Adj Close  \
  682 2020-09-17  267.549988  274.399994  266.679993  270.320007  264.393829   
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  
         Volume  Daily Returns  
  682  81570800      -0.015622  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  ,
            Date        Open        High         Low       Close   Adj Close  \
  683 2020-09-18  271.790009  272.089996  262.630005  266.869995  261.019531   
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  
         Volume  Daily Returns  
  683  86251100      -0.012762  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  ,
            Date        Open        High         Low       Close   Adj Close  \
  684 2020-09-21  262.470001  267.649994  260.109985  267.510010  261.645508   
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  
         Volume  Daily Returns  
  684  57168600       0.002398  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  ,
            Date        Open        High         Low       Close   Adj Close  \
  685 2020-09-22  269.989990  273.079987  266.540009  272.480011  266.506500   
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  
         Volume  Daily Returns  
  685  41128900       0.018579  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  ,
            Date        Open        High         Low       Close   Adj Close  \
  686 2020-09-23  272.149994  272.339996  263.250000  264.160004  258.368927   
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  
         Volume  Daily Returns  
  686  48837300      -0.030534  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  ,
            Date        Open        High         Low       Close   Adj Close  \
  687 2020-09-24  261.390015  268.700012  261.220001  265.390015  259.571991   
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  
         Volume  Daily Returns  
  687  70631700       0.004656  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  ,
            Date        Open        High         Low       Close   Adj Close  \
  688 2020-09-25  265.910004  272.399994  264.299988  271.559998  265.606689   
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  
         Volume  Daily Returns  
  688  55242400       0.023249  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  ,
            Date        Open        High         Low       Close   Adj Close  \
  689 2020-09-28  276.579987  277.200012  271.670013  277.200012  271.123108   
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  
         Volume  Daily Returns  
  689  58438300       0.020769  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  ,
            Date        Open        High         Low       Close   Adj Close  \
  690 2020-09-29  276.619995  277.709991  275.369995  275.950012  269.900421   
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  
         Volume  Daily Returns  
  690  27050000      -0.004510  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  ,
            Date        Open        High         Low       Close   Adj Close  \
  691 2020-09-30  276.149994  281.089996  275.869995  277.839996  271.749023   
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  
         Volume  Daily Returns  
  691  49380800       0.006849  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  ,
            Date        Open        High         Low       Close   Adj Close  \
  692 2020-10-01  281.790009  282.880005  279.839996  282.250000  276.062347   
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  
         Volume  Daily Returns  
  692  50020200       0.015872  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  ,
            Date        Open        High         Low       Close   Adj Close  \
  693 2020-10-02  276.019989  282.239990  273.440002  274.309998  268.296417   
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  
         Volume  Daily Returns  
  693  75497400      -0.028131  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  ,
            Date        Open        High         Low       Close   Adj Close  \
  694 2020-10-05  276.339996  280.489990  276.230011  280.160004  274.018158   
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  
         Volume  Daily Returns  
  694  28184600       0.021326  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  ,
            Date        Open        High         Low       Close   Adj Close  \
  695 2020-10-06  279.450012  281.190002  274.250000  275.160004  269.127808   
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  
         Volume  Daily Returns  
  695  49704200      -0.017847  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  ,
            Date        Open        High         Low       Close   Adj Close  \
  696 2020-10-07  277.890015  280.739990  277.279999  279.920013  273.783447   
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  
         Volume  Daily Returns  
  696  27539700       0.017299  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  ,
            Date        Open        High         Low       Close   Adj Close  \
  697 2020-10-08  282.399994  282.470001  280.309998  281.410004  275.240753   
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  
         Volume  Daily Returns  
  697  25443300       0.005323  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  ,
            Date        Open        High         Low       Close   Adj Close  \
  698 2020-10-09  283.109985  285.790009  282.709991  285.709991  279.446564   
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  
         Volume  Daily Returns  
  698  30201100       0.015280  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  ,
            Date        Open        High         Low       Close   Adj Close  \
  699 2020-10-12  290.549988  297.459991  289.470001  294.529999  288.073151   
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  
         Volume  Daily Returns  
  699  79370700       0.030870  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  ,
            Date        Open        High         Low       Close   Adj Close  \
  700 2020-10-13  296.390015  297.049988  293.109985  294.519989  288.063385   
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  
         Volume  Daily Returns  
  700  64240000      -0.000034  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  ,
            Date        Open        High         Low       Close   Adj Close  \
  701 2020-10-14  295.350006  296.350006  290.260010  292.059998  285.657288   
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  
         Volume  Daily Returns  
  701  36949100      -0.008353  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  ,
            Date        Open        High         Low       Close   Adj Close  \
  702 2020-10-15  287.200012  290.709991  286.540009  290.100006  283.740265   
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  
         Volume  Daily Returns  
  702  42514200      -0.006711  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  ,
            Date        Open        High         Low       Close   Adj Close  \
  703 2020-10-16  291.799988  293.269989  288.149994  288.510010  282.185150   
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  
         Volume  Daily Returns  
  703  40570700      -0.005481  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  ,
            Date        Open        High         Low       Close   Adj Close  \
  704 2020-10-19  290.489990  291.480011  282.790009  283.799988  277.578400   
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  
         Volume  Daily Returns  
  704  36756800      -0.016325  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  ,
            Date        Open        High         Low       Close   Adj Close  \
  705 2020-10-20  284.559998  287.619995  282.950012  284.410004  278.174988   
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  
         Volume  Daily Returns  
  705  32195400       0.002149  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  ,
            Date        Open        High         Low       Close   Adj Close  \
  706 2020-10-21  284.670013  287.320007  283.690002  284.190002  277.959869   
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  
         Volume  Daily Returns  
  706  29306100      -0.000773  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  ,
            Date        Open        High         Low       Close   Adj Close  \
  707 2020-10-22  285.049988  285.980011  280.820007  284.179993  277.950043   
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  
         Volume  Daily Returns  
  707  32196200      -0.000035  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  ,
            Date        Open        High         Low       Close   Adj Close  \
  708 2020-10-23  284.769989  284.910004  281.779999  284.739990  278.497803   
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  
         Volume  Daily Returns  
  708  24658500       0.001971  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  ,
            Date        Open        High         Low       Close   Adj Close  \
  709 2020-10-26  282.380005  285.299988  276.760010  280.470001  274.321381   
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  
         Volume  Daily Returns  
  709  38421100      -0.014996  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  ,
            Date        Open        High         Low       Close   Adj Close  \
  710 2020-10-27  281.500000  283.510010  280.200012  282.660004  276.463318   
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  
         Volume  Daily Returns  
  710  30559100       0.007808  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  ,
            Date        Open        High         Low       Close   Adj Close  \
  711 2020-10-28  278.010010  278.640015  271.380005  271.640015  265.684967   
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  
         Volume  Daily Returns  
  711  53413500      -0.038987  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  ,
            Date        Open        High         Low       Close   Adj Close  \
  712 2020-10-29  273.000000  279.489990  272.519989  276.390015  270.330841   
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  
         Volume  Daily Returns  
  712  43246300       0.017486  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  ,
            Date        Open        High         Low       Close   Adj Close  \
  713 2020-10-30  274.339996  275.239990  267.070007  269.380005  263.474487   
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  
         Volume  Daily Returns  
  713  65838300      -0.025363  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  ,
            Date        Open        High         Low       Close   Adj Close  \
  714 2020-11-02  271.850006  273.519989  266.970001  269.980011  264.061340   
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  
         Volume  Daily Returns  
  714  39987400       0.002227  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  ,
            Date        Open        High         Low       Close   Adj Close  \
  715 2020-11-03  271.959991  276.820007  270.839996  274.649994  268.628937   
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  
         Volume  Daily Returns  
  715  43604100       0.017297  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  ,
            Date        Open        High         Low       Close   Adj Close  \
  716 2020-11-04  283.589996  288.769989  281.869995  286.910004  280.620209   
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  
         Volume  Daily Returns  
  716  75728200       0.044639  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  ,
            Date        Open        High         Low       Close   Adj Close  \
  717 2020-11-05  293.529999  295.390015  292.000000  294.390015  287.936188   
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  
         Volume  Daily Returns  
  717  52054200       0.026071  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  ,
            Date        Open        High         Low       Close   Adj Close  \
  718 2020-11-06  293.709991  295.359985  289.829987  294.609985  288.151398   
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  
         Volume  Daily Returns  
  718  40959800       0.000747  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  ,
            Date        Open        High         Low       Close   Adj Close  \
  719 2020-11-09  297.649994  299.140015  288.119995  288.589996  282.263336   
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  
         Volume  Daily Returns  
  719  86537100      -0.020434  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  ,
            Date        Open        High         Low       Close   Adj Close  \
  720 2020-11-10  285.170013  286.660004  280.619995  283.420013  277.206726   
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  
         Volume  Daily Returns  
  720  69024900      -0.017915  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  ,
            Date        Open        High         Low       Close   Adj Close  \
  721 2020-11-11  286.029999  290.250000  283.380005  289.760010  283.407745   
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  
         Volume  Daily Returns  
  721  36102900       0.022370  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  ,
            Date        Open        High         Low       Close   Adj Close  \
  722 2020-11-12  290.760010  292.070007  287.250000  288.399994  282.077545   
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  
         Volume  Daily Returns  
  722  34414600      -0.004694  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  ,
            Date        Open        High         Low       Close   Adj Close  \
  723 2020-11-13  290.170013  291.570007  287.869995  290.929993  284.552063   
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  
         Volume  Daily Returns  
  723  24806900       0.008772  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  ,
            Date        Open        High         Low       Close   Adj Close  \
  724 2020-11-16  290.619995  293.510010  289.989990  293.200012  286.772308   
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  
         Volume  Daily Returns  
  724  30168400       0.007803  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  ,
            Date        Open        High         Low       Close   Adj Close  \
  725 2020-11-17  293.399994  293.739990  291.609985  292.269989  285.862640   
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  
         Volume  Daily Returns  
  725  21843500      -0.003172  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  ,
            Date        Open        High         Low       Close   Adj Close  \
  726 2020-11-18  291.700012  293.369995  290.019989  290.109985  283.750061   
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  
         Volume  Daily Returns  
  726  28069600      -0.007390  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  ,
            Date        Open        High         Low       Close   Adj Close  \
  727 2020-11-19  289.540009  292.700012  288.850006  292.380005  285.970245   
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  
         Volume  Daily Returns  
  727  22718400       0.007824  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  ,
            Date        Open        High         Low       Close   Adj Close  \
  728 2020-11-20  292.299988  293.070007  290.290009  290.380005  284.014069   
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  
         Volume  Daily Returns  
  728  25907300      -0.006840  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  ,
            Date        Open        High         Low       Close   Adj Close  \
  729 2020-11-23  291.410004  292.750000  288.070007  290.390015  284.023956   
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  
         Volume  Daily Returns  
  729  26875600       0.000035  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  ,
            Date        Open        High         Low       Close   Adj Close  \
  730 2020-11-24  291.489990  294.980011  289.630005  294.470001  288.014496   
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  
         Volume  Daily Returns  
  730  24516800       0.014050  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  ,
            Date        Open        High         Low       Close   Adj Close  \
  731 2020-11-25  295.570007  296.940002  294.589996  296.279999  289.784729   
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  
         Volume  Daily Returns  
  731  23326800       0.006146  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  ,
            Date        Open        High         Low       Close   Adj Close  \
  732 2020-11-27  298.309998  300.170013  297.899994  299.010010  292.454956   
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  
         Volume  Daily Returns  
  732  17163100       0.009215  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  ,
            Date        Open        High         Low       Close   Adj Close  \
  733 2020-11-30  299.339996  299.970001  294.779999  299.619995  293.051514   
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  
         Volume  Daily Returns  
  733  27836200       0.002040  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  ,
            Date        Open        High         Low       Close   Adj Close  \
  734 2020-12-01  301.970001  305.140015  300.829987  303.459991  296.807343   
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  
         Volume  Daily Returns  
  734  27521300       0.012816  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  ,
            Date        Open        High         Low       Close   Adj Close  \
  735 2020-12-02  302.250000  304.200012  300.350006  303.850006  297.188782   
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  
         Volume  Daily Returns  
  735  23620000       0.001285  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  ,
            Date        Open        High         Low       Close   Adj Close  \
  736 2020-12-03  304.170013  305.880005  303.529999  304.279999  297.609375   
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  
         Volume  Daily Returns  
  736  22828700       0.001415  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  ,
            Date        Open        High         Low       Close   Adj Close  \
  737 2020-12-04  304.329987  305.670013  303.630005  305.519989  298.822174   
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  
         Volume  Daily Returns  
  737  19332100       0.004075  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  ,
            Date        Open        High         Low       Close   Adj Close  \
  738 2020-12-07  305.709991  307.630005  305.519989  307.250000  300.514252   
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  
         Volume  Daily Returns  
  738  20851000       0.005662  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  ,
            Date        Open        High         Low       Close   Adj Close  \
  739 2020-12-08  306.760010  308.600006  304.950012  308.290009  301.531494   
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  
         Volume  Daily Returns  
  739  18341500       0.003385  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  ,
            Date        Open        High         Low       Close   Adj Close  \
  740 2020-12-09  308.070007  308.359985  300.209991  301.309998  294.704498   
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  
         Volume  Daily Returns  
  740  48839300      -0.022641  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  ,
            Date        Open        High         Low       Close   Adj Close  \
  741 2020-12-10  299.209991  303.679993  298.089996  302.519989  295.887970   
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  
         Volume  Daily Returns  
  741  27519500       0.004016  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  ,
            Date        Open        High         Low       Close   Adj Close  \
  742 2020-12-11  300.809998  301.980011  298.470001  301.850006  295.232666   
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  
         Volume  Daily Returns  
  742  26760400      -0.002215  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  ,
            Date        Open        High         Low       Close   Adj Close  \
  743 2020-12-14  303.079987  306.049988  303.010010  304.040009  297.374695   
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  
         Volume  Daily Returns  
  743  28804800       0.007255  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  ,
            Date        Open        High         Low       Close   Adj Close  \
  744 2020-12-15  306.369995  307.290009  304.109985  307.290009  300.553406   
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  
         Volume  Daily Returns  
  744  25709000       0.010689  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  ,
            Date        Open        High         Low       Close   Adj Close  \
  745 2020-12-16  307.700012  309.790009  306.619995  308.980011  302.206390   
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  
         Volume  Daily Returns  
  745  25461900       0.005500  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  ,
            Date        Open        High         Low       Close   Adj Close  \
  746 2020-12-17  310.630005  311.239990  309.390015  311.000000  304.182068   
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  
         Volume  Daily Returns  
  746  23730500       0.006538  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  ,
            Date        Open        High         Low       Close   Adj Close  \
  747 2020-12-18  311.660004  311.980011  307.609985  310.059998  303.262695   
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  
         Volume  Daily Returns  
  747  41173400      -0.003022  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  ,
            Date        Open        High         Low       Close   Adj Close  \
  748 2020-12-21  306.459991  309.470001  303.600006  308.920013  302.695343   
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  
         Volume  Daily Returns  
  748  37095500      -0.001871  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  ,
            Date        Open        High         Low       Close   Adj Close  \
  749 2020-12-22  309.850006  310.709991  306.850006  309.760010  303.518463   
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  
         Volume  Daily Returns  
  749  26176300       0.002719  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  ,
            Date        Open        High         Low       Close   Adj Close  \
  750 2020-12-23  309.809998  310.179993  308.040009  308.200012  301.989838   
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  
         Volume  Daily Returns  
  750  21201300      -0.005036  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  ,
            Date        Open        High         Low       Close   Adj Close  \
  751 2020-12-24  308.470001  310.019989  308.390015  309.559998  303.322418   
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  
         Volume  Daily Returns  
  751  16785000       0.004413  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  ,
            Date        Open        High         Low       Close   Adj Close  \
  752 2020-12-28  312.250000  313.170013  310.359985  312.679993  306.379547   
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  
         Volume  Daily Returns  
  752  22497700       0.010079  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  ,
            Date        Open        High         Low       Close   Adj Close  \
  753 2020-12-29  314.049988  314.690002  312.029999  312.959991  306.653900   
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  
         Volume  Daily Returns  
  753  25871900       0.000895  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  ,
            Date        Open        High         Low       Close   Adj Close  \
  754 2020-12-30  314.160004  314.489990  312.329987  312.970001  306.663727   
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  
         Volume  Daily Returns  
  754  18138100       0.000032  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  ,
            Date        Open        High         Low       Close   Adj Close  \
  755 2020-12-31  312.869995  314.239990  311.760010  313.739990  307.418213   
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  
         Volume  Daily Returns  
  755  21611400       0.002460  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  ,
            Date        Open        High         Low       Close   Adj Close  \
  756 2021-01-04  315.109985  315.290009  305.179993  309.309998  303.077484   
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  
         Volume  Daily Returns  
  756  45305900      -0.014120  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  ,
            Date        Open        High         Low       Close   Adj Close  \
  757 2021-01-05  308.290009  312.140015  308.290009  311.859985  305.576080   
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  
         Volume  Daily Returns  
  757  29323400       0.008244  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  ,
            Date        Open        High         Low       Close   Adj Close  \
  758 2021-01-06  307.000000  311.880005  305.980011  307.540009  301.343140   
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  
         Volume  Daily Returns  
  758  52809600      -0.013852  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  ,
            Date        Open        High         Low       Close   Adj Close  \
  759 2021-01-07  310.279999  315.839996  310.250000  314.980011  308.633240   
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  
         Volume  Daily Returns  
  759  30394800       0.024192  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  ,
            Date        Open        High         Low       Close   Adj Close  \
  760 2021-01-08  317.339996  319.390015  315.079987  319.029999  312.601624   
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  
         Volume  Daily Returns  
  760  33955800       0.012858  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  ,
            Date        Open        High         Low       Close   Adj Close  \
  761 2021-01-11  315.980011  317.190002  313.750000  314.420013  308.084564   
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  
         Volume  Daily Returns  
  761  32746400      -0.014450  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  
  790  97241900      -0.002977  ,
            Date        Open        High         Low       Close   Adj Close  \
  762 2021-01-12  314.459991  315.579987  311.200012  313.920013  307.594574   
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  
         Volume  Daily Returns  
  762  29266800      -0.001590  
  763  22898400       0.006753  
  764  23500100      -0.005347  
  765  35118700      -0.007921  
  766  24537000       0.014590  
  767  30728100       0.023261  
  768  25130600       0.008000  
  769  21609400      -0.002880  
  770  39080600       0.008266  
  771  25498100       0.001463  
  772  55264000      -0.027877  
  773  42836300       0.005917  
  774  55259000      -0.021038  
  775  35646000       0.024987  
  776  33930800       0.016314  
  777  24824500      -0.003967  
  778  22350900       0.011827  
  779  22732000       0.003392  
  780  20462800       0.006700  
  781  17597500      -0.000210  
  782  28068700      -0.002279  
  783  22046100       0.005500  
  784  20346800       0.005589  
  785  27080800      -0.002705  
  786  31360300      -0.004799  
  787  32236200      -0.004372  
  788  39157700      -0.004361  
  789  47256900      -0.025920  
  790  97241900      -0.002977  
  791  58206300       0.008243  ,
            Date        Open        High         Low       Close   Adj Close  \
  763 2021-01-13  314.190002  316.859985  313.570007  316.040009  309.671844   
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  
          Volume  Daily Returns  
  763   22898400       0.006753  
  764   23500100      -0.005347  
  765   35118700      -0.007921  
  766   24537000       0.014590  
  767   30728100       0.023261  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  ,
            Date        Open        High         Low       Close   Adj Close  \
  764 2021-01-14  316.500000  317.529999  313.859985  314.350006  308.015900   
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  
          Volume  Daily Returns  
  764   23500100      -0.005347  
  765   35118700      -0.007921  
  766   24537000       0.014590  
  767   30728100       0.023261  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  ,
            Date        Open        High         Low       Close   Adj Close  \
  765 2021-01-15  314.130005  315.119995  310.579987  311.859985  305.576080   
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  
          Volume  Daily Returns  
  765   35118700      -0.007921  
  766   24537000       0.014590  
  767   30728100       0.023261  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  ,
            Date        Open        High         Low       Close   Adj Close  \
  766 2021-01-19  314.250000  316.929993  313.119995  316.410004  310.034424   
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  
          Volume  Daily Returns  
  766   24537000       0.014590  
  767   30728100       0.023261  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  ,
            Date        Open        High         Low       Close   Adj Close  \
  767 2021-01-20  320.140015  324.739990  316.510010  323.769989  317.246063   
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  
          Volume  Daily Returns  
  767   30728100       0.023261  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  ,
            Date        Open        High         Low       Close   Adj Close  \
  768 2021-01-21  325.149994  327.130005  323.730011  326.359985  319.783905   
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  
          Volume  Daily Returns  
  768   25130600       0.008000  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  ,
            Date        Open        High         Low       Close   Adj Close  \
  769 2021-01-22  325.290009  326.459991  324.709991  325.420013  318.862854   
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  
          Volume  Daily Returns  
  769   21609400      -0.002880  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  ,
            Date        Open        High         Low       Close   Adj Close  \
  770 2021-01-25  328.910004  330.320007  321.410004  328.109985  321.498688   
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  
          Volume  Daily Returns  
  770   39080600       0.008266  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  ,
            Date        Open        High         Low       Close   Adj Close  \
  771 2021-01-26  328.850006  329.760010  327.220001  328.589996  321.968994   
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  
          Volume  Daily Returns  
  771   25498100       0.001463  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  ,
            Date        Open        High         Low       Close   Adj Close  \
  772 2021-01-27  326.260010  326.269989  317.359985  319.429993  312.993561   
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  
          Volume  Daily Returns  
  772   55264000      -0.027877  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  ,
            Date        Open        High         Low       Close   Adj Close  \
  773 2021-01-28  320.670013  326.420013  320.029999  321.320007  314.845459   
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  
          Volume  Daily Returns  
  773   42836300       0.005917  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  ,
            Date        Open        High         Low       Close   Adj Close  \
  774 2021-01-29  319.579987  320.720001  312.760010  314.559998  308.221741   
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  
          Volume  Daily Returns  
  774   55259000      -0.021038  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  ,
            Date        Open        High         Low       Close   Adj Close  \
  775 2021-02-01  318.109985  323.540009  316.019989  322.420013  315.923340   
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  
          Volume  Daily Returns  
  775   35646000       0.024987  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  ,
            Date        Open        High         Low       Close   Adj Close  \
  776 2021-02-02  325.480011  328.869995  325.309998  327.679993  321.077332   
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  
          Volume  Daily Returns  
  776   33930800       0.016314  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  ,
            Date        Open        High         Low       Close   Adj Close  \
  777 2021-02-03  329.820007  330.200012  326.320007  326.380005  319.803528   
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  
          Volume  Daily Returns  
  777   24824500      -0.003967  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  ,
            Date        Open        High         Low       Close   Adj Close  \
  778 2021-02-04  327.820007  330.329987  326.459991  330.239990  323.585724   
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  
          Volume  Daily Returns  
  778   22350900       0.011827  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  ,
            Date        Open        High         Low       Close   Adj Close  \
  779 2021-02-05  331.220001  332.399994  329.529999  331.359985  324.683197   
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  
          Volume  Daily Returns  
  779   22732000       0.003392  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  ,
            Date        Open        High         Low       Close   Adj Close  \
  780 2021-02-08  333.100006  333.739990  331.410004  333.579987  326.858429   
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  
          Volume  Daily Returns  
  780   20462800       0.006700  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  ,
            Date        Open        High         Low       Close   Adj Close  \
  781 2021-02-09  332.619995  334.809998  332.609985  333.510010  326.789856   
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  
          Volume  Daily Returns  
  781   17597500      -0.000210  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  ,
            Date        Open        High         Low       Close   Adj Close  \
  782 2021-02-10  334.989990  335.459991  329.500000  332.750000  326.045197   
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  
          Volume  Daily Returns  
  782   28068700      -0.002279  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  ,
            Date        Open        High         Low       Close   Adj Close  \
  783 2021-02-11  334.329987  335.000000  332.119995  334.579987  327.838287   
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  
          Volume  Daily Returns  
  783   22046100       0.005500  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  ,
            Date        Open        High         Low       Close   Adj Close  \
  784 2021-02-12  333.709991  336.619995  332.630005  336.450012  329.670654   
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  
          Volume  Daily Returns  
  784   20346800       0.005589  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  ,
            Date        Open        High         Low       Close   Adj Close  \
  785 2021-02-16  337.269989  338.190002  334.339996  335.540009  328.779022   
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  
          Volume  Daily Returns  
  785   27080800      -0.002705  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  ,
            Date        Open        High         Low       Close   Adj Close  \
  786 2021-02-17  332.470001  335.660004  330.170013  333.929993  327.201355   
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  
          Volume  Daily Returns  
  786   31360300      -0.004799  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  ,
            Date        Open        High         Low       Close   Adj Close  \
  787 2021-02-18  330.230011  333.869995  328.359985  332.470001  325.770813   
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  
          Volume  Daily Returns  
  787   32236200      -0.004372  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  ,
            Date        Open        High         Low       Close   Adj Close  \
  788 2021-02-19  333.859985  333.989990  329.970001  331.019989  324.350037   
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  
          Volume  Daily Returns  
  788   39157700      -0.004361  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  ,
            Date        Open        High         Low       Close   Adj Close  \
  789 2021-02-22  326.500000  327.799988  322.230011  322.440002  315.942902   
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  
          Volume  Daily Returns  
  789   47256900      -0.025920  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  ,
            Date        Open        High         Low       Close   Adj Close  \
  790 2021-02-23  317.000000  323.200012  311.000000  321.480011  315.002289   
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  
          Volume  Daily Returns  
  790   97241900      -0.002977  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  ,
            Date        Open        High         Low       Close   Adj Close  \
  791 2021-02-24  318.739990  324.450012  315.959991  324.130005  317.598846   
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  
          Volume  Daily Returns  
  791   58206300       0.008243  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  ,
            Date        Open        High         Low       Close   Adj Close  \
  792 2021-02-25  321.390015  324.029999  311.239990  312.829987  306.526550   
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  
          Volume  Daily Returns  
  792  110182600      -0.034863  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  ,
            Date        Open        High         Low       Close   Adj Close  \
  793 2021-02-26  315.850006  319.109985  310.880005  314.140015  307.810181   
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  
          Volume  Daily Returns  
  793  104739800       0.004188  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  ,
            Date        Open        High         Low       Close   Adj Close  \
  794 2021-03-01  319.269989  323.940002  317.940002  323.589996  317.069702   
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  
          Volume  Daily Returns  
  794   49164500       0.030082  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  
  823   25833000      -0.001305  ,
            Date        Open        High         Low       Close   Adj Close  \
  795 2021-03-02  324.250000  324.329987  318.140015  318.399994  311.984283   
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  
          Volume  Daily Returns  
  795   48370000      -0.016039  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  
  823   25833000      -0.001305  
  824   30374000       0.011673  ,
            Date        Open        High         Low       Close   Adj Close  \
  796 2021-03-03  317.269989  318.239990  309.100006  309.160004  302.930573   
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  
          Volume  Daily Returns  
  796   86301100      -0.029020  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  
  823   25833000      -0.001305  
  824   30374000       0.011673  
  825   42564300      -0.012009  ,
            Date        Open        High         Low       Close   Adj Close  \
  797 2021-03-04  308.779999  312.040009  300.109985  304.100006  297.972473   
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  
          Volume  Daily Returns  
  797  139131600      -0.016367  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  
  823   25833000      -0.001305  
  824   30374000       0.011673  
  825   42564300      -0.012009  
  826   36342800       0.015156  ,
            Date        Open        High         Low       Close   Adj Close  \
  798 2021-03-05  306.799988  309.609985  297.450012  308.679993  302.460175   
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  
          Volume  Daily Returns  
  798  121523700       0.015061  
  799   88409800      -0.028314  
  800   80391100       0.039441  
  801   76798100      -0.002855  
  802   53484800       0.023031  
  803   69315600      -0.008112  
  804   42955700       0.010683  
  805   54925900       0.005489  
  806   78258700       0.004117  
  807   82718100      -0.030630  
  808   78446200       0.003525  
  809   56194800       0.018753  
  810   53455400      -0.004363  
  811   64803700      -0.016865  
  812   78729000      -0.001731  
  813   63519600       0.015000  
  814   54608000      -0.000285  
  815   44635700      -0.005033  
  816   55032500       0.015303  
  817   55685600       0.017046  
  818   42172500       0.019965  
  819   33537200      -0.000695  
  820   32046400       0.002418  
  821   29940800       0.010434  
  822   36664900       0.006058  
  823   25833000      -0.001305  
  824   30374000       0.011673  
  825   42564300      -0.012009  
  826   36342800       0.015156  
  827   40860100       0.001171  ,
            Date        Open        High         Low       Close   Adj Close  \
  799 2021-03-08  308.119995  310.059998  299.510010  299.940002  293.896332   
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  
         Volume  Daily Returns  
  799  88409800      -0.028314  
  800  80391100       0.039441  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  ,
            Date        Open        High         Low       Close   Adj Close  \
  800 2021-03-09  307.470001  313.730011  306.920013  311.769989  305.487915   
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  
         Volume  Daily Returns  
  800  80391100       0.039441  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  ,
            Date        Open        High         Low       Close   Adj Close  \
  801 2021-03-10  316.160004  316.470001  310.170013  310.880005  304.615875   
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  
         Volume  Daily Returns  
  801  76798100      -0.002855  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  ,
            Date        Open        High         Low       Close   Adj Close  \
  802 2021-03-11  315.769989  319.859985  314.850006  318.040009  311.631592   
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  
         Volume  Daily Returns  
  802  53484800       0.023031  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  ,
            Date        Open        High         Low       Close   Adj Close  \
  803 2021-03-12  313.859985  318.230011  311.390015  315.459991  309.103577   
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  
         Volume  Daily Returns  
  803  69315600      -0.008112  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  ,
            Date        Open        High         Low       Close   Adj Close  \
  804 2021-03-15  315.790009  319.000000  314.100006  318.829987  312.405609   
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  
         Volume  Daily Returns  
  804  42955700       0.010683  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  ,
            Date        Open        High         Low       Close   Adj Close  \
  805 2021-03-16  321.089996  324.200012  319.100006  320.579987  314.120392   
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  
         Volume  Daily Returns  
  805  54925900       0.005489  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  ,
            Date        Open        High         Low       Close   Adj Close  \
  806 2021-03-17  317.450012  323.850006  315.679993  321.899994  315.413757   
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  
         Volume  Daily Returns  
  806  78258700       0.004117  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  ,
            Date        Open        High         Low       Close   Adj Close  \
  807 2021-03-18  316.869995  317.880005  311.570007  312.040009  305.752502   
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  
         Volume  Daily Returns  
  807  82718100      -0.030630  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  ,
            Date        Open        High         Low       Close   Adj Close  \
  808 2021-03-19  311.869995  314.730011  309.660004  313.140015  306.830292   
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  
         Volume  Daily Returns  
  808  78446200       0.003525  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  ,
            Date        Open        High         Low       Close   Adj Close  \
  809 2021-03-22  315.209991  320.739990  315.209991  318.609985  312.584351   
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  
         Volume  Daily Returns  
  809  56194800       0.018753  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  ,
            Date        Open        High         Low       Close   Adj Close  \
  810 2021-03-23  319.730011  321.089996  316.380005  317.220001  311.220673   
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  
         Volume  Daily Returns  
  810  53455400      -0.004363  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  ,
            Date        Open        High         Low       Close   Adj Close  \
  811 2021-03-24  318.630005  318.670013  311.720001  311.869995  305.971802   
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  
         Volume  Daily Returns  
  811  64803700      -0.016865  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  ,
            Date        Open        High         Low       Close   Adj Close  \
  812 2021-03-25  309.970001  312.890015  307.390015  311.329987  305.442047   
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  
         Volume  Daily Returns  
  812  78729000      -0.001731  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  ,
            Date        Open        High         Low       Close   Adj Close  \
  813 2021-03-26  311.109985  316.329987  309.670013  316.000000  310.023773   
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  
         Volume  Daily Returns  
  813  63519600       0.015000  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  ,
            Date        Open        High         Low       Close   Adj Close  \
  814 2021-03-29  315.450012  316.989990  312.470001  315.910004  309.935455   
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  
         Volume  Daily Returns  
  814  54608000      -0.000285  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  ,
            Date        Open        High         Low       Close   Adj Close  \
  815 2021-03-30  313.890015  314.910004  311.540009  314.320007  308.375549   
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  
         Volume  Daily Returns  
  815  44635700      -0.005033  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  ,
            Date        Open        High         Low       Close   Adj Close  \
  816 2021-03-31  316.160004  320.739990  315.809998  319.130005  313.094604   
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  
         Volume  Daily Returns  
  816  55032500       0.015303  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  ,
            Date        Open        High         Low       Close   Adj Close  \
  817 2021-04-01  323.070007  324.709991  322.809998  324.570007  318.431641   
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  
         Volume  Daily Returns  
  817  55685600       0.017046  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  ,
            Date        Open        High         Low       Close   Adj Close  \
  818 2021-04-05  327.130005  331.839996  326.880005  331.049988  324.789124   
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  
         Volume  Daily Returns  
  818  42172500       0.019965  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  ,
            Date        Open        High         Low       Close   Adj Close  \
  819 2021-04-06  330.730011  332.829987  330.019989  330.820007  324.563507   
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  
         Volume  Daily Returns  
  819  33537200      -0.000695  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  ,
            Date        Open        High         Low       Close   Adj Close  \
  820 2021-04-07  330.329987  332.480011  329.369995  331.619995  325.348267   
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  
         Volume  Daily Returns  
  820  32046400       0.002418  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  ,
            Date        Open        High         Low       Close   Adj Close  \
  821 2021-04-08  334.559998  335.269989  333.739990  335.079987  328.742889   
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  
         Volume  Daily Returns  
  821  29940800       0.010434  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  ,
            Date        Open        High         Low       Close   Adj Close  \
  822 2021-04-09  333.679993  337.320007  332.920013  337.109985  330.734528   
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  
         Volume  Daily Returns  
  822  36664900       0.006058  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  ,
            Date        Open        High         Low       Close   Adj Close  \
  823 2021-04-12  336.040009  337.100006  334.730011  336.670013  330.302917   
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  
         Volume  Daily Returns  
  823  25833000      -0.001305  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  ,
            Date        Open        High         Low       Close   Adj Close  \
  824 2021-04-13  338.239990  341.079987  338.019989  340.600006  334.158600   
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  
         Volume  Daily Returns  
  824  30374000       0.011673  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  ,
            Date        Open        High         Low       Close   Adj Close  \
  825 2021-04-14  340.850006  340.980011  335.670013  336.510010  330.145844   
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  
         Volume  Daily Returns  
  825  42564300      -0.012009  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  ,
            Date        Open        High         Low       Close   Adj Close  \
  826 2021-04-15  339.470001  342.010010  336.220001  341.609985  335.149414   
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  
         Volume  Daily Returns  
  826  36342800       0.015156  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  ,
            Date        Open        High         Low       Close   Adj Close  \
  827 2021-04-16  342.149994  342.230011  340.079987  342.010010  335.541901   
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  
         Volume  Daily Returns  
  827  40860100       0.001171  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  ,
            Date        Open        High         Low       Close   Adj Close  \
  828 2021-04-19  340.390015  341.579987  336.899994  338.880005  332.471039   
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  
         Volume  Daily Returns  
  828  34533100      -0.009152  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  ,
            Date        Open        High         Low       Close   Adj Close  \
  829 2021-04-20  338.200012  339.519989  334.380005  336.410004  330.047729   
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  
         Volume  Daily Returns  
  829  38081800      -0.007289  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  ,
            Date        Open        High         Low       Close   Adj Close  \
  830 2021-04-21  335.089996  339.480011  333.970001  339.290009  332.873322   
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  
         Volume  Daily Returns  
  830  36598100       0.008561  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  ,
            Date        Open        High         Low       Close   Adj Close  \
  831 2021-04-22  338.890015  339.899994  334.010010  335.200012  328.860657   
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  
         Volume  Daily Returns  
  831  45936100      -0.012055  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  ,
            Date        Open        High         Low       Close   Adj Close  \
  832 2021-04-23  335.850006  340.769989  335.850006  339.420013  333.000885   
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  
         Volume  Daily Returns  
  832  36381900       0.012590  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  ,
            Date        Open        High         Low       Close   Adj Close  \
  833 2021-04-26  339.670013  341.920013  338.899994  341.630005  335.169067   
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  
         Volume  Daily Returns  
  833  30812000       0.006511  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  ,
            Date        Open        High         Low       Close   Adj Close  \
  834 2021-04-27  341.929993  342.149994  339.170013  340.149994  333.717041   
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  
         Volume  Daily Returns  
  834  33187200      -0.004332  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  ,
            Date        Open        High         Low       Close   Adj Close  \
  835 2021-04-28  339.809998  340.850006  338.329987  339.000000  332.588745   
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  
         Volume  Daily Returns  
  835  33615700      -0.003381  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  ,
            Date        Open        High         Low       Close   Adj Close  \
  836 2021-04-29  342.369995  342.799988  336.899994  340.220001  333.785736   
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  
         Volume  Daily Returns  
  836  37708900       0.003599  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  ,
            Date        Open        High         Low       Close   Adj Close  \
  837 2021-04-30  337.700012  340.260010  337.049988  337.989990  331.597870   
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  
         Volume  Daily Returns  
  837  38263400      -0.006555  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  ,
            Date        Open        High         Low       Close   Adj Close  \
  838 2021-05-03  339.230011  340.000000  335.730011  336.190002  329.831879   
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  
         Volume  Daily Returns  
  838  29729700      -0.005326  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  ,
            Date        Open        High         Low       Close   Adj Close  \
  839 2021-05-04  333.559998  333.890015  326.209991  330.140015  323.896362   
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  
         Volume  Daily Returns  
  839  65147000      -0.017996  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  ,
            Date        Open        High         Low       Close   Adj Close  \
  840 2021-05-05  332.250000  333.140015  328.230011  329.029999  322.807343   
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  
         Volume  Daily Returns  
  840  46219300      -0.003362  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  ,
            Date        Open        High         Low       Close   Adj Close  \
  841 2021-05-06  328.760010  331.670013  326.450012  331.510010  325.240387   
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  
         Volume  Daily Returns  
  841  46814300       0.007537  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  ,
            Date        Open        High         Low       Close   Adj Close  \
  842 2021-05-07  334.369995  336.649994  331.690002  334.200012  327.879547   
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  
         Volume  Daily Returns  
  842  53324500       0.008114  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  ,
            Date        Open        High         Low       Close   Adj Close  \
  843 2021-05-10  332.779999  332.959991  325.549988  325.760010  319.599213   
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  
         Volume  Daily Returns  
  843  60700500      -0.025254  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  ,
            Date        Open        High         Low       Close   Adj Close  \
  844 2021-05-11  319.700012  326.130005  319.019989  325.309998  319.157654   
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  
         Volume  Daily Returns  
  844  71963600      -0.001382  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  ,
            Date        Open        High         Low       Close   Adj Close  \
  845 2021-05-12  320.230011  322.619995  316.000000  316.890015  310.896973   
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  
         Volume  Daily Returns  
  845  91164900      -0.025883  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  ,
            Date        Open        High         Low       Close   Adj Close  \
  846 2021-05-13  319.920013  322.399994  316.899994  319.339996  313.300598   
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  
         Volume  Daily Returns  
  846  69877800       0.007731  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  ,
            Date        Open        High         Low       Close   Adj Close  \
  847 2021-05-14  322.600006  327.329987  322.079987  326.390015  320.217255   
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  
         Volume  Daily Returns  
  847  44370000       0.022077  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  ,
            Date        Open        High         Low       Close   Adj Close  \
  848 2021-05-17  324.630005  326.369995  321.450012  324.410004  318.274719   
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  
         Volume  Daily Returns  
  848  39395000      -0.006066  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  ,
            Date        Open        High         Low       Close   Adj Close  \
  849 2021-05-18  325.390015  326.649994  321.940002  322.220001  316.126099   
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  
         Volume  Daily Returns  
  849  36528500      -0.006751  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  ,
            Date        Open        High         Low       Close   Adj Close  \
  850 2021-05-19  316.660004  322.899994  316.299988  322.589996  316.489075   
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  
         Volume  Daily Returns  
  850  66319100       0.001148  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  ,
            Date        Open        High         Low       Close   Adj Close  \
  851 2021-05-20  324.119995  329.709991  323.890015  328.829987  322.611145   
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  
         Volume  Daily Returns  
  851  46466100       0.019344  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  ,
            Date        Open        High         Low       Close   Adj Close  \
  852 2021-05-21  330.429993  330.859985  326.640015  327.010010  320.825500   
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  
         Volume  Daily Returns  
  852  50330400      -0.005535  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  ,
            Date        Open        High         Low       Close   Adj Close  \
  853 2021-05-24  329.369995  333.670013  326.899994  332.510010  326.221527   
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  
         Volume  Daily Returns  
  853  32475800       0.016819  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  ,
            Date        Open        High         Low       Close   Adj Close  \
  854 2021-05-25  334.070007  334.809998  331.760010  332.970001  326.672852   
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  
         Volume  Daily Returns  
  854  31280300       0.001383  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  ,
            Date        Open        High         Low       Close   Adj Close  \
  855 2021-05-26  333.660004  334.609985  332.950012  334.130005  327.810883   
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  
         Volume  Daily Returns  
  855  25444900       0.003484  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  ,
            Date        Open        High         Low       Close   Adj Close  \
  856 2021-05-27  333.670013  334.540009  332.670013  332.880005  326.584503   
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  
         Volume  Daily Returns  
  856  27931700      -0.003741  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  ,
            Date        Open        High         Low       Close   Adj Close  \
  857 2021-05-28  334.119995  335.570007  333.600006  333.929993  327.614655   
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  
         Volume  Daily Returns  
  857  29927400       0.003154  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  ,
            Date        Open        High         Low       Close   Adj Close  \
  858 2021-06-01  335.299988  335.790009  331.429993  332.820007  326.525635   
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  
         Volume  Daily Returns  
  858  31145400      -0.003324  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  ,
            Date        Open        High         Low       Close   Adj Close  \
  859 2021-06-02  333.250000  334.339996  331.700012  333.470001  327.163361   
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  
         Volume  Daily Returns  
  859  22047900       0.001953  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  ,
            Date        Open        High         Low       Close   Adj Close  \
  860 2021-06-03  330.549988  331.859985  328.279999  330.000000  323.758972   
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  
         Volume  Daily Returns  
  860  37057800      -0.010406  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  ,
            Date        Open        High         Low       Close   Adj Close  \
  861 2021-06-04  331.850006  336.059998  331.779999  335.600006  329.253113   
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  
         Volume  Daily Returns  
  861  38736500       0.016970  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  ,
            Date        Open        High         Low       Close   Adj Close  \
  862 2021-06-07  335.049988  336.660004  334.339996  336.600006  330.234131   
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  
         Volume  Daily Returns  
  862  32611900       0.002980  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  ,
            Date        Open        High         Low       Close   Adj Close  \
  863 2021-06-08  338.399994  339.290009  335.029999  336.760010  330.391144   
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  
         Volume  Daily Returns  
  863  27282800       0.000475  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  ,
            Date        Open        High         Low       Close   Adj Close  \
  864 2021-06-09  338.170013  338.970001  336.649994  336.839996  330.469635   
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  
         Volume  Daily Returns  
  864  21485300       0.000238  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  ,
            Date        Open        High         Low       Close   Adj Close  \
  865 2021-06-10  337.190002  340.459991  336.730011  340.350006  333.913269   
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  
         Volume  Daily Returns  
  865  33702100       0.010420  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  ,
            Date        Open        High         Low       Close   Adj Close  \
  866 2021-06-11  340.359985  341.250000  339.690002  341.239990  334.786377   
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  
         Volume  Daily Returns  
  866  21222800       0.002615  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  ,
            Date        Open        High         Low       Close   Adj Close  \
  867 2021-06-14  341.679993  344.519989  340.459991  344.510010  337.994568   
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  
         Volume  Daily Returns  
  867  27827700       0.009583  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  ,
            Date        Open        High         Low       Close   Adj Close  \
  868 2021-06-15  344.149994  344.470001  341.519989  342.260010  335.787109   
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  
         Volume  Daily Returns  
  868  35963800      -0.006531  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  ,
            Date        Open        High         Low       Close   Adj Close  \
  869 2021-06-16  342.739990  343.839996  337.450012  341.010010  334.560760   
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  
         Volume  Daily Returns  
  869  55399500      -0.003652  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  ,
            Date        Open        High         Low       Close   Adj Close  \
  870 2021-06-17  339.970001  346.380005  339.920013  345.339996  338.808868   
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  
         Volume  Daily Returns  
  870  59722700       0.012698  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  ,
            Date        Open        High         Low       Close   Adj Close  \
  871 2021-06-18  343.630005  344.809998  341.859985  342.630005  336.150146   
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  
         Volume  Daily Returns  
  871  55414900      -0.007847  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  ,
            Date        Open        High         Low       Close   Adj Close  \
  872 2021-06-21  342.429993  344.690002  340.149994  344.359985  338.239288   
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  
         Volume  Daily Returns  
  872  32992600       0.006215  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  ,
            Date        Open        High         Low       Close   Adj Close  \
  873 2021-06-22  344.149994  348.029999  343.839996  347.570007  341.392242   
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  
         Volume  Daily Returns  
  873  28941600       0.009322  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  ,
            Date        Open        High         Low       Close   Adj Close  \
  874 2021-06-23  347.510010  348.920013  346.880005  347.739990  341.559296   
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  
         Volume  Daily Returns  
  874  27188500       0.000489  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  ,
            Date        Open        High         Low       Close   Adj Close  \
  875 2021-06-24  349.730011  351.459991  349.170013  349.890015  343.671051   
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  
         Volume  Daily Returns  
  875  32581600       0.006183  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  ,
            Date        Open        High         Low       Close   Adj Close  \
  876 2021-06-25  350.470001  350.720001  348.839996  349.459991  343.248627   
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  
         Volume  Daily Returns  
  876  28682800      -0.001229  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  ,
            Date        Open        High         Low       Close   Adj Close  \
  877 2021-06-28  350.779999  353.850006  350.720001  353.709991  347.423126   
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  
         Volume  Daily Returns  
  877  39130300       0.012162  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  ,
            Date        Open        High         Low       Close   Adj Close  \
  878 2021-06-29  353.529999  355.019989  352.670013  354.989990  348.680359   
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  
         Volume  Daily Returns  
  878  29426000       0.003619  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  ,
            Date        Open        High         Low       Close   Adj Close  \
  879 2021-06-30  354.829987  355.230011  353.829987  354.429993  348.130310   
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  
         Volume  Daily Returns  
  879  32724000      -0.001578  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  ,
            Date        Open        High         Low       Close   Adj Close  \
  880 2021-07-01  354.070007  355.089996  352.679993  354.570007  348.267822   
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  
         Volume  Daily Returns  
  880  29290000       0.000395  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  ,
            Date        Open        High         Low       Close   Adj Close  \
  881 2021-07-02  356.519989  358.970001  356.279999  358.640015  352.265472   
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  
         Volume  Daily Returns  
  881  32727200       0.011479  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  ,
            Date        Open        High         Low       Close   Adj Close  \
  882 2021-07-06  359.260010  360.480011  356.489990  360.190002  353.787964   
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  
         Volume  Daily Returns  
  882  38842400       0.004322  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  ,
            Date        Open        High         Low       Close   Adj Close  \
  883 2021-07-07  362.450012  362.760010  358.940002  360.950012  354.534393   
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  
         Volume  Daily Returns  
  883  35265200       0.002110  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  ,
            Date        Open        High         Low       Close   Adj Close  \
  884 2021-07-08  355.739990  359.649994  354.420013  358.769989  352.393158   
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  
         Volume  Daily Returns  
  884  50890000      -0.006040  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  ,
            Date        Open        High         Low       Close   Adj Close  \
  885 2021-07-09  358.170013  361.500000  357.570007  361.010010  354.593414   
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  
         Volume  Daily Returns  
  885  35184500       0.006244  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  ,
            Date        Open        High         Low       Close   Adj Close  \
  886 2021-07-12  362.450012  362.890015  360.829987  362.420013  355.978241   
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  
         Volume  Daily Returns  
  886  25717700       0.003905  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  ,
            Date        Open        High         Low       Close   Adj Close  \
  887 2021-07-13  362.029999  365.470001  361.540009  362.420013  355.978241   
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  
         Volume  Daily Returns  
  887  39723000       0.000000  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  ,
            Date        Open        High         Low       Close   Adj Close  \
  888 2021-07-14  364.829987  365.489990  362.220001  363.070007  356.616760   
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  
         Volume  Daily Returns  
  888  35336400       0.001794  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  ,
            Date        Open        High         Low       Close   Adj Close  \
  889 2021-07-15  362.980011  363.190002  358.459991  360.519989  354.112061   
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  
         Volume  Daily Returns  
  889  53391600      -0.007024  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  ,
            Date        Open        High         Low       Close   Adj Close  \
  890 2021-07-16  361.399994  362.410004  357.239990  357.600006  351.243958   
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  
         Volume  Daily Returns  
  890  47262000      -0.008099  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  ,
            Date        Open        High         Low       Close   Adj Close  \
  891 2021-07-19  354.049988  355.179993  352.040009  354.670013  348.366058   
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  
         Volume  Daily Returns  
  891  64404600      -0.008193  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  ,
            Date        Open        High         Low       Close   Adj Close  \
  892 2021-07-20  355.630005  360.279999  353.799988  358.790009  352.412811   
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  
         Volume  Daily Returns  
  892  42183700       0.011616  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  ,
            Date        Open        High         Low       Close   Adj Close  \
  893 2021-07-21  358.350006  361.559998  358.119995  361.559998  355.133606   
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  
         Volume  Daily Returns  
  893  30259900       0.007720  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  ,
            Date        Open        High         Low       Close   Adj Close  \
  894 2021-07-22  361.769989  363.959991  361.769989  363.950012  357.481140   
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  
         Volume  Daily Returns  
  894  30252200       0.006610  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  ,
            Date        Open        High         Low       Close   Adj Close  \
  895 2021-07-23  365.309998  368.489990  363.920013  368.200012  361.655579   
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  
         Volume  Daily Returns  
  895  31960800       0.011677  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  ,
            Date        Open        High         Low       Close   Adj Close  \
  896 2021-07-26  367.489990  368.890015  366.600006  368.489990  361.940460   
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  
         Volume  Daily Returns  
  896  28438100       0.000788  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  ,
            Date        Open        High         Low       Close   Adj Close  \
  897 2021-07-27  368.220001  368.220001  360.160004  364.429993  357.952545   
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  
         Volume  Daily Returns  
  897  57933100      -0.011018  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  ,
            Date        Open        High         Low       Close   Adj Close  \
  898 2021-07-28  365.600006  367.450012  363.239990  365.829987  359.327698   
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  
         Volume  Daily Returns  
  898  42066200       0.003842  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  ,
            Date        Open        High         Low       Close   Adj Close  \
  899 2021-07-29  365.250000  367.679993  365.250000  366.480011  359.966156   
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  
         Volume  Daily Returns  
  899  25672500       0.001777  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  ,
            Date        Open        High         Low       Close   Adj Close  \
  900 2021-07-30  362.440002  365.170013  362.410004  364.570007  358.090118   
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  
         Volume  Daily Returns  
  900  36484600      -0.005212  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  ,
            Date        Open        High         Low       Close   Adj Close  \
  901 2021-08-02  366.279999  366.880005  363.869995  364.600006  358.119537   
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  
         Volume  Daily Returns  
  901  27334100       0.000082  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  ,
            Date        Open        High         Low       Close   Adj Close  \
  902 2021-08-03  365.279999  366.929993  362.000000  366.809998  360.290283   
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  
         Volume  Daily Returns  
  902  35558500       0.006062  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  ,
            Date        Open        High         Low       Close   Adj Close  \
  903 2021-08-04  366.769989  368.320007  365.630005  367.339996  360.810852   
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  
         Volume  Daily Returns  
  903  29602200       0.001445  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  ,
            Date        Open        High         Low       Close   Adj Close  \
  904 2021-08-05  368.179993  369.910004  367.450012  369.670013  363.099487   
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  
         Volume  Daily Returns  
  904  21443900       0.006343  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  ,
            Date        Open        High         Low       Close   Adj Close  \
  905 2021-08-06  368.369995  369.369995  366.910004  368.049988  361.508148   
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  
         Volume  Daily Returns  
  905  33332100      -0.004383  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  ,
            Date        Open        High         Low       Close   Adj Close  \
  906 2021-08-09  368.519989  369.269989  367.390015  368.730011  362.176178   
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  
         Volume  Daily Returns  
  906  25960200       0.001848  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  ,
            Date        Open        High         Low       Close   Adj Close  \
  907 2021-08-10  369.260010  369.559998  365.619995  366.839996  360.319672   
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  
         Volume  Daily Returns  
  907  35130800      -0.005126  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  ,
            Date        Open        High         Low       Close   Adj Close  \
  908 2021-08-11  368.140015  368.649994  364.839996  366.209991  359.700928   
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  
         Volume  Daily Returns  
  908  34249800      -0.001717  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  ,
            Date        Open        High         Low       Close   Adj Close  \
  909 2021-08-12  365.690002  367.899994  364.299988  367.529999  360.997467   
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  
         Volume  Daily Returns  
  909  25969200       0.003604  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  ,
            Date        Open        High         Low       Close   Adj Close  \
  910 2021-08-13  367.890015  369.160004  367.380005  368.820007  362.264557   
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  
         Volume  Daily Returns  
  910  19336200       0.003510  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  ,
            Date        Open        High         Low       Close   Adj Close  \
  911 2021-08-16  367.670013  369.019989  363.700012  368.980011  362.421722   
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  
         Volume  Daily Returns  
  911  34856900       0.000434  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  ,
            Date        Open        High         Low       Close   Adj Close  \
  912 2021-08-17  366.149994  367.149994  363.230011  365.730011  359.229431   
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  
         Volume  Daily Returns  
  912  44793900      -0.008808  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  ,
            Date        Open        High         Low       Close   Adj Close  \
  913 2021-08-18  365.179993  366.619995  361.869995  362.209991  355.772034   
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  
         Volume  Daily Returns  
  913  38541900      -0.009624  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  ,
            Date        Open        High         Low       Close   Adj Close  \
  914 2021-08-19  360.220001  365.679993  359.959991  363.959991  357.490936   
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  
         Volume  Daily Returns  
  914  48499400       0.004831  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  ,
            Date        Open        High         Low       Close   Adj Close  \
  915 2021-08-20  365.059998  368.140015  364.739990  367.730011  361.193970   
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  
         Volume  Daily Returns  
  915  39486000       0.010358  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  ,
            Date        Open        High         Low       Close   Adj Close  \
  916 2021-08-23  368.799988  373.940002  368.790009  373.230011  366.596191   
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  
         Volume  Daily Returns  
  916  34034700       0.014957  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  ,
            Date        Open        High         Low       Close   Adj Close  \
  917 2021-08-24  373.839996  374.989990  373.359985  374.369995  367.715881   
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  
         Volume  Daily Returns  
  917  21732900       0.003054  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  ,
            Date        Open        High         Low       Close   Adj Close  \
  918 2021-08-25  374.630005  375.390015  373.859985  374.799988  368.138275   
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  
         Volume  Daily Returns  
  918  20441900       0.001149  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  ,
            Date        Open        High         Low       Close   Adj Close  \
  919 2021-08-26  373.920013  374.619995  371.970001  372.420013  365.800568   
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  
         Volume  Daily Returns  
  919  29133300      -0.006350  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  ,
            Date        Open        High         Low       Close   Adj Close  \
  920 2021-08-27  373.070007  376.559998  372.570007  376.040009  369.356262   
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  
         Volume  Daily Returns  
  920  27104700       0.009720  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  ,
            Date        Open        High         Low       Close   Adj Close  \
  921 2021-08-30  376.850006  380.760010  376.829987  380.260010  373.501221   
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  
         Volume  Daily Returns  
  921  27295700       0.011222  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  ,
            Date        Open        High         Low       Close   Adj Close  \
  922 2021-08-31  380.510010  380.579987  378.359985  379.950012  373.196716   
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  
         Volume  Daily Returns  
  922  29628200      -0.000815  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  ,
            Date        Open        High         Low       Close   Adj Close  \
  923 2021-09-01  381.040009  382.709991  380.369995  380.579987  373.815491   
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  
         Volume  Daily Returns  
  923  28138300       0.001658  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  ,
            Date        Open        High         Low       Close   Adj Close  \
  924 2021-09-02  381.970001  382.309998  379.149994  380.399994  373.638733   
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  
         Volume  Daily Returns  
  924  25453400      -0.000473  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  ,
            Date        Open        High         Low       Close   Adj Close  \
  925 2021-09-03  379.220001  381.980011  379.200012  381.570007  374.787933   
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  
         Volume  Daily Returns  
  925  24605400       0.003076  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  ,
            Date        Open        High         Low       Close   Adj Close  \
  926 2021-09-07  381.679993  382.779999  380.489990  382.109985  375.318268   
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  
         Volume  Daily Returns  
  926  23970200       0.001415  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  ,
            Date        Open        High         Low       Close   Adj Close  \
  927 2021-09-08  381.929993  381.929993  378.450012  380.779999  374.011993   
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  
         Volume  Daily Returns  
  927  32949200      -0.003480  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  ,
            Date        Open        High         Low       Close   Adj Close  \
  928 2021-09-09  381.010010  382.149994  379.220001  379.470001  372.725311   
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  
         Volume  Daily Returns  
  928  29399000      -0.003440  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  ,
            Date        Open        High         Low       Close   Adj Close  \
  929 2021-09-10  381.230011  381.970001  376.250000  376.589996  369.896454   
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  
         Volume  Daily Returns  
  929  40249400      -0.007590  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  ,
            Date        Open        High         Low       Close   Adj Close  \
  930 2021-09-13  378.989990  379.429993  374.220001  376.329987  369.641083   
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  
         Volume  Daily Returns  
  930  48741800      -0.000690  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  ,
            Date        Open        High         Low       Close   Adj Close  \
  931 2021-09-14  377.859985  378.609985  374.279999  375.260010  368.590057   
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  
         Volume  Daily Returns  
  931  41826600      -0.002843  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  ,
            Date        Open        High         Low       Close   Adj Close  \
  932 2021-09-15  375.730011  378.410004  373.369995  378.049988  371.330505   
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  
         Volume  Daily Returns  
  932  34097900       0.007435  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  ,
            Date        Open        High         Low       Close   Adj Close  \
  933 2021-09-16  376.679993  378.899994  374.700012  378.309998  371.585876   
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  
         Volume  Daily Returns  
  933  35193100       0.000688  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  ,
            Date        Open        High         Low       Close   Adj Close  \
  934 2021-09-17  377.820007  377.869995  372.760010  373.829987  367.185486   
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  
         Volume  Daily Returns  
  934  60912300      -0.011842  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  ,
            Date        Open        High         Low       Close   Adj Close  \
  935 2021-09-20  367.459991  369.250000  360.929993  365.700012  359.598267   
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  
         Volume  Daily Returns  
  935  76203200      -0.020663  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  ,
            Date        Open        High         Low       Close   Adj Close  \
  936 2021-09-21  367.579987  368.809998  364.989990  366.149994  360.040741   
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  
         Volume  Daily Returns  
  936  41927500       0.001230  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  ,
            Date        Open        High         Low       Close   Adj Close  \
  937 2021-09-22  367.089996  371.070007  365.959991  369.570007  363.403625   
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  
         Volume  Daily Returns  
  937  46972900       0.009340  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  ,
            Date        Open        High         Low       Close   Adj Close  \
  938 2021-09-23  370.760010  374.040009  370.100006  372.980011  366.756805   
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  
         Volume  Daily Returns  
  938  44652000       0.009227  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  ,
            Date        Open        High         Low       Close   Adj Close  \
  939 2021-09-24  370.649994  373.760010  370.269989  373.329987  367.100922   
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  
         Volume  Daily Returns  
  939  36056800       0.000938  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  ,
            Date        Open        High         Low       Close   Adj Close  \
  940 2021-09-27  370.200012  371.250000  367.730011  370.350006  364.170654   
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  
         Volume  Daily Returns  
  940  43338100      -0.007982  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  ,
            Date        Open        High         Low       Close   Adj Close  \
  941 2021-09-28  365.670013  370.299988  359.350006  359.869995  353.865509   
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  
         Volume  Daily Returns  
  941  97701600      -0.028298  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  ,
            Date        Open        High         Low       Close   Adj Close  \
  942 2021-09-29  361.170013  363.369995  358.640015  359.279999  353.285400   
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  
         Volume  Daily Returns  
  942  58076600      -0.001639  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  ,
            Date        Open        High         Low       Close   Adj Close  \
  943 2021-09-30  360.970001  362.679993  357.100006  357.959991  351.987366   
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  
         Volume  Daily Returns  
  943  61384600      -0.003674  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  ,
            Date        Open        High         Low       Close   Adj Close  \
  944 2021-10-01  358.600006  361.250000  354.380005  360.179993  354.170319   
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  
         Volume  Daily Returns  
  944  56375500       0.006202  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  ,
            Date        Open        High         Low       Close   Adj Close  \
  945 2021-10-04  358.519989  358.859985  350.320007  352.619995  346.736511   
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  
         Volume  Daily Returns  
  945  76766000      -0.020989  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  ,
            Date        Open        High         Low       Close   Adj Close  \
  946 2021-10-05  353.709991  359.690002  353.480011  357.380005  351.417114   
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  
         Volume  Daily Returns  
  946  47232900       0.013499  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  ,
            Date        Open        High         Low       Close   Adj Close  \
  947 2021-10-06  354.079987  359.950012  353.149994  359.670013  353.668854   
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  
         Volume  Daily Returns  
  947  56806500       0.006408  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  ,
            Date        Open        High         Low       Close   Adj Close  \
  948 2021-10-07  362.799988  365.690002  362.250000  362.970001  356.913788   
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  
         Volume  Daily Returns  
  948  39411200       0.009175  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  ,
            Date        Open        High         Low       Close   Adj Close  \
  949 2021-10-08  364.079987  364.320007  360.609985  361.160004  355.134003   
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  
         Volume  Daily Returns  
  949  41822300      -0.004987  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  ,
            Date        Open        High         Low       Close   Adj Close  \
  950 2021-10-11  359.579987  363.200012  358.299988  358.390015  352.410248   
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  
         Volume  Daily Returns  
  950  34847200      -0.007670  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  ,
            Date        Open        High         Low       Close   Adj Close  \
  951 2021-10-12  359.880005  360.329987  356.480011  357.140015  351.181091   
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  
         Volume  Daily Returns  
  951  43905100      -0.003488  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  ,
            Date        Open        High         Low       Close   Adj Close  \
  952 2021-10-13  359.510010  360.690002  357.429993  360.000000  353.993378   
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  
         Volume  Daily Returns  
  952  40120800       0.008008  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  ,
            Date        Open        High         Low       Close   Adj Close  \
  953 2021-10-14  363.690002  366.850006  363.010010  366.630005  360.512726   
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  
         Volume  Daily Returns  
  953  43433900       0.018417  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  ,
            Date        Open        High         Low       Close   Adj Close  \
  954 2021-10-15  367.880005  369.059998  366.820007  368.940002  362.784210   
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  
         Volume  Daily Returns  
  954  40419900       0.006301  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  ,
            Date        Open        High         Low       Close   Adj Close  \
  955 2021-10-18  367.609985  372.869995  366.989990  372.649994  366.432281   
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  
         Volume  Daily Returns  
  955  34513500       0.010056  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  ,
            Date        Open        High         Low       Close   Adj Close  \
  956 2021-10-19  373.750000  375.519989  372.700012  375.470001  369.205261   
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  
         Volume  Daily Returns  
  956  29091000       0.007568  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  ,
            Date        Open        High         Low       Close   Adj Close  \
  957 2021-10-20  375.940002  376.570007  373.459991  374.980011  368.723419   
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  
         Volume  Daily Returns  
  957  31390300      -0.001305  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  
  986  77766500      -0.017013  ,
            Date        Open        High         Low       Close   Adj Close  \
  958 2021-10-21  374.160004  377.470001  373.850006  377.269989  370.975189   
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  
         Volume  Daily Returns  
  958  25469300       0.006107  
  959  36275800      -0.008403  
  960  32597800       0.010238  
  961  47191300       0.003149  
  962  45760500       0.002321  
  963  38007000       0.011105  
  964  37310100       0.004919  
  965  30765300       0.003419  
  966  25135300       0.004181  
  967  33748900       0.010616  
  968  40265300       0.012818  
  969  43383800       0.000954  
  970  29256300      -0.001355  
  971  50490700      -0.006883  
  972  54937400      -0.014697  
  973  32243000       0.002773  
  974  34730600       0.010523  
  975  33716900      -0.000228  
  976  27872900       0.007121  
  977  28703300       0.000528  
  978  45721500       0.010362  
  979  45191700       0.005576  
  980  61715400      -0.011609  
  981  70098700      -0.004558  
  982  46954400       0.003220  
  983  51533300      -0.018959  
  984  54447100       0.021703  
  985  81332700      -0.014686  
  986  77766500      -0.017013  
  987  84416600       0.007207  ,
            Date        Open        High         Low       Close   Adj Close  \
  959 2021-10-22  375.980011  376.970001  372.390015  374.100006  367.858063   
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  
          Volume  Daily Returns  
  959   36275800      -0.008403  
  960   32597800       0.010238  
  961   47191300       0.003149  
  962   45760500       0.002321  
  963   38007000       0.011105  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  ,
            Date        Open        High         Low       Close   Adj Close  \
  960 2021-10-25  375.559998  378.869995  373.559998  377.929993  371.624176   
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  
          Volume  Daily Returns  
  960   32597800       0.010238  
  961   47191300       0.003149  
  962   45760500       0.002321  
  963   38007000       0.011105  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  ,
            Date        Open        High         Low       Close   Adj Close  \
  961 2021-10-26  380.230011  382.709991  377.910004  379.119995  372.794312   
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  
          Volume  Daily Returns  
  961   47191300       0.003149  
  962   45760500       0.002321  
  963   38007000       0.011105  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  ,
            Date        Open        High         Low       Close   Adj Close  \
  962 2021-10-27  379.579987  383.149994  379.309998  380.000000  373.659668   
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  
          Volume  Daily Returns  
  962   45760500       0.002321  
  963   38007000       0.011105  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  ,
            Date        Open        High         Low       Close   Adj Close  \
  963 2021-10-28  381.950012  384.480011  381.160004  384.220001  377.809265   
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  
          Volume  Daily Returns  
  963   38007000       0.011105  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  ,
            Date        Open        High         Low       Close   Adj Close  \
  964 2021-10-29  381.059998  386.279999  380.700012  386.109985  379.667633   
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  
          Volume  Daily Returns  
  964   37310100       0.004919  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  
  993   52545800       0.010871  ,
            Date        Open        High         Low       Close   Adj Close  \
  965 2021-11-01  386.559998  387.559998  384.420013  387.429993  380.965698   
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  
          Volume  Daily Returns  
  965   30765300       0.003419  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  
  993   52545800       0.010871  
  994   50166400      -0.014447  ,
            Date        Open        High         Low       Close   Adj Close  \
  966 2021-11-02  386.799988  389.540009  386.750000  389.049988  382.558624   
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  
          Volume  Daily Returns  
  966   25135300       0.004181  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  
  993   52545800       0.010871  
  994   50166400      -0.014447  
  995   75199200      -0.010350  ,
            Date        Open        High         Low       Close   Adj Close  \
  967 2021-11-03  389.549988  393.609985  388.480011  393.179993  386.619720   
  968 2021-11-04  394.480011  399.200012  393.920013  398.220001  391.575592   
  969 2021-11-05  400.040009  400.989990  397.160004  398.600006  391.949341   
  970 2021-11-08  398.570007  399.619995  397.399994  398.059998  391.418335   
  971 2021-11-09  399.160004  399.570007  393.920013  395.320007  388.724030   
  972 2021-11-10  392.470001  395.359985  387.529999  389.510010  383.010986   
  973 2021-11-11  392.570007  392.750000  390.239990  390.589996  384.072937   
  974 2021-11-12  391.769989  395.250000  390.130005  394.700012  388.114380   
  975 2021-11-15  395.910004  396.239990  392.100006  394.609985  388.025848   
  976 2021-11-16  393.859985  397.929993  393.660004  397.420013  390.789032   
  977 2021-11-17  397.750000  399.720001  396.640015  397.630005  390.995453   
  978 2021-11-18  399.730011  402.269989  397.450012  401.750000  395.046783   
  979 2021-11-19  403.429993  405.299988  402.579987  403.989990  397.249420   
  980 2021-11-22  405.570007  408.709991  399.190002  399.299988  392.637604   
  981 2021-11-23  398.109985  400.230011  392.920013  397.480011  390.847992   
  982 2021-11-24  394.929993  399.049988  392.540009  398.760010  392.106659   
  983 2021-11-26  396.109985  397.540009  389.769989  391.200012  384.672760   
  984 2021-11-29  395.890015  400.730011  395.140015  399.690002  393.021149   
  985 2021-11-30  398.779999  401.190002  391.750000  393.820007  387.249115   
  986 2021-12-01  398.279999  400.480011  386.640015  387.119995  380.660889   
  987 2021-12-02  385.799988  391.739990  384.339996  389.910004  383.404297   
  988 2021-12-03  391.309998  392.339996  378.899994  383.130005  376.737457   
  989 2021-12-06  383.630005  387.600006  379.299988  386.200012  379.756287   
  990 2021-12-07  393.029999  398.459991  392.989990  397.829987  391.192169   
  991 2021-12-08  398.170013  399.820007  396.220001  399.609985  392.942413   
  992 2021-12-09  398.350006  400.200012  393.529999  393.730011  387.160553   
  993 2021-12-10  396.619995  398.279999  393.359985  398.010010  391.369202   
  994 2021-12-13  398.000000  398.329987  391.880005  392.260010  385.715088   
  995 2021-12-14  387.299988  390.089996  383.630005  388.200012  381.722839   
  996 2021-12-15  387.940002  397.420013  383.880005  397.049988  390.425140   
  
          Volume  Daily Returns  
  967   33748900       0.010616  
  968   40265300       0.012818  
  969   43383800       0.000954  
  970   29256300      -0.001355  
  971   50490700      -0.006883  
  972   54937400      -0.014697  
  973   32243000       0.002773  
  974   34730600       0.010523  
  975   33716900      -0.000228  
  976   27872900       0.007121  
  977   28703300       0.000528  
  978   45721500       0.010362  
  979   45191700       0.005576  
  980   61715400      -0.011609  
  981   70098700      -0.004558  
  982   46954400       0.003220  
  983   51533300      -0.018959  
  984   54447100       0.021703  
  985   81332700      -0.014686  
  986   77766500      -0.017013  
  987   84416600       0.007207  
  988  105349100      -0.017389  
  989   67588800       0.008013  
  990   56005300       0.030114  
  991   39204000       0.004474  
  992   49973700      -0.014714  
  993   52545800       0.010871  
  994   50166400      -0.014447  
  995   75199200      -0.010350  
  996   73858000       0.022797  ,
  ...]}
In [34]:
# Adjust the merge to ensure we include the announcement date accurately by merging on exact dates and including previous rates
# First, sort the unemployment data and ETF data by date to ensure continuity
unemployment_data = unemployment_data.sort_values('Date')
iwm_data = iwm_data.sort_values('Date')
qqq_data = qqq_data.sort_values('Date')
spy_data = spy_data.sort_values('Date')

# Function to adjust the event and estimation windows to focus on the exact announcement dates
def adjust_windows(event_df, full_df, days_event=5, days_estimation=30):
    # Find dates that exactly match the announcement dates
    announcement_dates = event_df['Date'].unique()
    windows_data = {'Event Window': [], 'Estimation Window': []}

    for adate in announcement_dates:
        # Identify the exact index for announcement date in full ETF data
        if adate in full_df['Date'].values:
            event_idx = full_df[full_df['Date'] == adate].index[0]

            # Calculate indices for event window with boundary checks
            max_idx = len(full_df) - 1
            min_idx = 0
            start_event = max(min_idx, event_idx - 2)
            end_event = min(max_idx, event_idx + 2)
            event_window = full_df.iloc[start_event:end_event + 1]

            # Calculate indices for estimation window with boundary checks
            start_estimation = max(min_idx, event_idx - days_estimation - 2)
            end_estimation = max(min_idx, event_idx - 3)
            estimation_window = full_df.iloc[start_estimation:end_estimation + 1]

            windows_data['Event Window'].append(event_window)
            windows_data['Estimation Window'].append(estimation_window)

    return windows_data

# Apply adjustments for each ETF
adjusted_iwm = adjust_windows(unemployment_data, iwm_data)
adjusted_qqq = adjust_windows(unemployment_data, qqq_data)
adjusted_spy = adjust_windows(unemployment_data, spy_data)

# Check the first adjusted event and estimation window for QQQ as an example
adjusted_qqq['Event Window'][0].head(), adjusted_qqq['Estimation Window'][0].head()
Out[34]:
(        Date        Open        High         Low       Close   Adj Close  \
 0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
 1 2018-01-03  158.639999  160.169998  158.610001  160.029999  153.347641   
 2 2018-01-04  160.580002  160.789993  160.080002  160.309998  153.615906   
 
      Volume  Daily Returns  
 0  32573300            NaN  
 1  29383600       0.009717  
 2  24776100       0.001749  ,
         Date        Open        High         Low       Close   Adj Close  \
 0 2018-01-02  156.559998  158.529999  156.169998  158.490005  151.871933   
 
      Volume  Daily Returns  
 0  32573300            NaN  )
In [36]:
# Recalculate expected returns and analyze the impact of unemployment rate announcements, considering abnormal daily returns

# Function to compute expected and abnormal returns
def calculate_expected_and_abnormal_returns(windows_data):
    results = []

    for event_window, estimation_window in zip(windows_data['Event Window'], windows_data['Estimation Window']):
        if not estimation_window.empty:
            # Calculate the mean and standard deviation of daily returns in the estimation window
            mean_return = estimation_window['Daily Returns'].mean()
            std_dev = estimation_window['Daily Returns'].std()

            # Calculate abnormal returns in the event window
            event_window['Expected Return'] = mean_return
            event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
            event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan

            results.append(event_window)

    return results

# Apply the calculations for each ETF
results_iwm = calculate_expected_and_abnormal_returns(adjusted_iwm)
results_qqq = calculate_expected_and_abnormal_returns(adjusted_qqq)
results_spy = calculate_expected_and_abnormal_returns(adjusted_spy)

# Output an example of calculated results for QQQ
results_qqq[0]  # Display the results of the first event analysis for QQQ as an example
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
IOPub data rate exceeded.
The notebook server will temporarily stop sending output
to the client in order to avoid crashing it.
To change this limit, set the config variable
`--NotebookApp.iopub_data_rate_limit`.

Current values:
NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)
NotebookApp.rate_limit_window=3.0 (secs)

C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'] = mean_return
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3453566094.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
Out[36]:
Date Open High Low Close Adj Close Volume Daily Returns Expected Return Abnormal Return Standardized Abnormal Return
0 2018-01-02 156.559998 158.529999 156.169998 158.490005 151.871933 32573300 NaN NaN NaN NaN
1 2018-01-03 158.639999 160.169998 158.610001 160.029999 153.347641 29383600 0.009717 NaN NaN NaN
2 2018-01-04 160.580002 160.789993 160.080002 160.309998 153.615906 24776100 0.001749 NaN NaN NaN
In [37]:
# Function to fill NaN values in the expected returns using the closest available values
def fill_na_and_recalculate_returns(results):
    filled_results = []
    for event_window in results:
        if not event_window.empty:
            # Fill NaN values in 'Expected Return' with the closest non-NaN values
            event_window['Expected Return'].fillna(method='ffill', inplace=True)
            event_window['Expected Return'].fillna(method='bfill', inplace=True)  # If NaN at the start

            # Recalculate abnormal and standardized abnormal returns
            event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
            std_dev = event_window['Daily Returns'].std()
            event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan

            filled_results.append(event_window)

    return filled_results

# Apply the NaN filling and recalculation for each ETF
filled_results_iwm = fill_na_and_recalculate_returns(results_iwm)
filled_results_qqq = fill_na_and_recalculate_returns(results_qqq)
filled_results_spy = fill_na_and_recalculate_returns(results_spy)

# Output an example of recalculated results for QQQ
filled_results_qqq[0]  # Display the results of the first event analysis for QQQ as an example
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:7: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  event_window['Expected Return'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:7: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  event_window['Expected Return'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:7: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:8: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  event_window['Expected Return'].fillna(method='bfill', inplace=True)  # If NaN at the start
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:8: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  event_window['Expected Return'].fillna(method='bfill', inplace=True)  # If NaN at the start
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:8: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Expected Return'].fillna(method='bfill', inplace=True)  # If NaN at the start
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:11: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Abnormal Return'] = event_window['Daily Returns'] - event_window['Expected Return']
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\1868711259.py:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  event_window['Standardized Abnormal Return'] = event_window['Abnormal Return'] / std_dev if std_dev else np.nan
Out[37]:
Date Open High Low Close Adj Close Volume Daily Returns Expected Return Abnormal Return Standardized Abnormal Return
0 2018-01-02 156.559998 158.529999 156.169998 158.490005 151.871933 32573300 NaN NaN NaN NaN
1 2018-01-03 158.639999 160.169998 158.610001 160.029999 153.347641 29383600 0.009717 NaN NaN NaN
2 2018-01-04 160.580002 160.789993 160.080002 160.309998 153.615906 24776100 0.001749 NaN NaN NaN
In [24]:
# Plotting line graphs for Adjusted Close prices of IWM, QQQ, and SPY
plt.figure(figsize=(14, 7))
plt.plot(IWM['Date'], IWM['Adj Close'], label='IWM', marker='o', markersize=4)
plt.plot(QQQ['Date'], QQQ['Adj Close'], label='QQQ', marker='x', markersize=4)
plt.plot(SPY['Date'], SPY['Adj Close'], label='SPY', marker='s', markersize=4)
plt.title('Adjusted Closing Prices of ETFs Over Time')
plt.xlabel('Date')
plt.ylabel('Adjusted Close Price (USD)')
plt.legend()
plt.grid(True)
plt.show()

Let's rename the columns before merging

In [6]:
QQQ.rename(columns={col: f"QQQ_{col}" for col in QQQ.columns if col != "Date"}, inplace=True)
IWM.rename(columns={col: f"IWM_{col}" for col in IWM.columns if col != "Date"}, inplace=True)
SPY.rename(columns={col: f"SPY_{col}" for col in SPY.columns if col != "Date"}, inplace=True)

# QQQ.columns=['QQQ_'+ column for column in QQQ.columns]
# IWM.columns= ['IWM_'+col for col in IWM.columns]
# IWM.columns= ['IWM_'+col for col in IWM.columns]
print(QQQ.columns, SPY.columns, IWM.columns)
Index(['Date', 'QQQ_Open', 'QQQ_High', 'QQQ_Low', 'QQQ_Close', 'QQQ_Adj Close',
       'QQQ_Volume'],
      dtype='object') Index(['Date', 'SPY_Open', 'SPY_High', 'SPY_Low', 'SPY_Close', 'SPY_Adj Close',
       'SPY_Volume'],
      dtype='object') Index(['Date', 'IWM_Open', 'IWM_High', 'IWM_Low', 'IWM_Close', 'IWM_Adj Close',
       'IWM_Volume'],
      dtype='object')
In [7]:
SPY
Out[7]:
Date SPY_Open SPY_High SPY_Low SPY_Close SPY_Adj Close SPY_Volume
0 1/2/2018 267.839996 268.809998 267.399994 268.769989 242.319351 86655700
1 1/3/2018 268.959991 270.640015 268.959991 270.470001 243.852097 90070400
2 1/4/2018 271.200012 272.160004 270.540009 271.609985 244.879929 80636400
3 1/5/2018 272.510010 273.559998 271.950012 273.420013 246.511826 83524000
4 1/8/2018 273.309998 274.100006 272.980011 273.920013 246.962494 57319200
... ... ... ... ... ... ... ...
1580 4/15/2024 515.130005 515.299988 503.579987 504.450012 504.450012 92101400
1581 4/16/2024 504.940002 506.500000 502.209991 503.529999 503.529999 73484000
1582 4/17/2024 506.049988 506.220001 499.119995 500.549988 500.549988 75910300
1583 4/18/2024 501.980011 504.130005 498.559998 499.519989 499.519989 74548100
1584 4/19/2024 499.440002 500.459991 493.859985 495.160004 495.160004 102129100

1585 rows × 7 columns

Let's make sure the dates are in the right format

In [8]:
SPY['Date'] = pd.to_datetime(SPY['Date'])
QQQ['Date'] = pd.to_datetime(SPY['Date'])
IWM['Date'] = pd.to_datetime(SPY['Date'])
unemployment['Date'] = pd.to_datetime(unemployment['Date'])
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3070950256.py:4: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  unemployment['Date'] = pd.to_datetime(unemployment['Date'])
In [9]:
stock1 = pd.merge(SPY, QQQ, on='Date', how='outer')
stock = pd.merge(stock1, IWM, on='Date', how='outer')
stock
Out[9]:
Date SPY_Open SPY_High SPY_Low SPY_Close SPY_Adj Close SPY_Volume QQQ_Open QQQ_High QQQ_Low QQQ_Close QQQ_Adj Close QQQ_Volume IWM_Open IWM_High IWM_Low IWM_Close IWM_Adj Close IWM_Volume
0 2018-01-02 267.839996 268.809998 267.399994 268.769989 242.319351 86655700 156.559998 158.529999 156.169998 158.490005 151.871933 32573300 153.199997 153.970001 152.460007 153.899994 141.990631 20489600
1 2018-01-03 268.959991 270.640015 268.959991 270.470001 243.852097 90070400 158.639999 160.169998 158.610001 160.029999 153.347641 29383600 153.869995 154.460007 153.520004 154.059998 142.138260 21836600
2 2018-01-04 271.200012 272.160004 270.540009 271.609985 244.879929 80636400 160.580002 160.789993 160.080002 160.309998 153.615906 24776100 154.970001 155.149994 154.020004 154.470001 142.516525 14207100
3 2018-01-05 272.510010 273.559998 271.950012 273.420013 246.511826 83524000 161.070007 162.029999 160.770004 161.919998 155.158768 26992300 154.880005 154.979996 153.940002 154.789993 142.811752 19883900
4 2018-01-08 273.309998 274.100006 272.980011 273.920013 246.962494 57319200 161.919998 162.630005 161.860001 162.550003 155.762390 23159100 154.729996 155.270004 153.500000 155.029999 143.033173 18457300
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1580 2024-04-15 515.130005 515.299988 503.579987 504.450012 504.450012 92101400 442.059998 442.149994 430.209991 431.059998 431.059998 63453600 199.369995 200.229996 194.979996 195.779999 195.779999 41119300
1581 2024-04-16 504.940002 506.500000 502.209991 503.529999 503.529999 73484000 430.899994 433.760010 429.700012 431.100006 431.100006 47619000 194.410004 196.240005 193.360001 195.059998 195.059998 43267500
1582 2024-04-17 506.049988 506.220001 499.119995 500.549988 500.549988 75910300 433.100006 433.119995 424.899994 425.839996 425.839996 56880500 196.470001 196.619995 192.990005 193.000000 193.000000 38589500
1583 2024-04-18 501.980011 504.130005 498.559998 499.519989 499.519989 74548100 426.489990 428.239990 422.829987 423.410004 423.410004 46549400 193.699997 195.660004 192.149994 192.839996 192.839996 40238200
1584 2024-04-19 499.440002 500.459991 493.859985 495.160004 495.160004 102129100 422.220001 422.750000 413.070007 414.649994 414.649994 75136600 191.940002 194.389999 191.339996 193.139999 193.139999 42499200

1585 rows × 19 columns

In [10]:
unemployment.rename(columns={col: f"unemployment_{col}" for col in unemployment.columns if col != "Date"}, inplace=True)
unemployment
Out[10]:
Date unemployment_Actual unemployment_Forecast unemployment_Previous
0 2024-04-05 3.80% 3.90% 3.90%
1 2024-03-08 3.90% 3.70% 3.70%
2 2024-02-02 3.70% 3.80% 3.70%
3 2024-01-05 3.70% 3.80% 3.70%
4 2023-12-08 3.70% 3.90% 3.90%
... ... ... ... ...
71 2018-05-04 3.90% 4.00% 4.10%
72 2018-04-06 4.10% 4.00% 4.10%
73 2018-03-09 4.10% 4.00% 4.10%
74 2018-02-02 4.10% 4.10% 4.10%
75 2018-01-05 4.10% 4.10% 4.10%

76 rows × 4 columns

In [11]:
data=pd.merge(stock, unemployment, on='Date', how='outer')
data
Out[11]:
Date SPY_Open SPY_High SPY_Low SPY_Close SPY_Adj Close SPY_Volume QQQ_Open QQQ_High QQQ_Low ... QQQ_Volume IWM_Open IWM_High IWM_Low IWM_Close IWM_Adj Close IWM_Volume unemployment_Actual unemployment_Forecast unemployment_Previous
0 2018-01-02 267.839996 268.809998 267.399994 268.769989 242.319351 86655700.0 156.559998 158.529999 156.169998 ... 32573300.0 153.199997 153.970001 152.460007 153.899994 141.990631 20489600.0 NaN NaN NaN
1 2018-01-03 268.959991 270.640015 268.959991 270.470001 243.852097 90070400.0 158.639999 160.169998 158.610001 ... 29383600.0 153.869995 154.460007 153.520004 154.059998 142.138260 21836600.0 NaN NaN NaN
2 2018-01-04 271.200012 272.160004 270.540009 271.609985 244.879929 80636400.0 160.580002 160.789993 160.080002 ... 24776100.0 154.970001 155.149994 154.020004 154.470001 142.516525 14207100.0 NaN NaN NaN
3 2018-01-05 272.510010 273.559998 271.950012 273.420013 246.511826 83524000.0 161.070007 162.029999 160.770004 ... 26992300.0 154.880005 154.979996 153.940002 154.789993 142.811752 19883900.0 4.10% 4.10% 4.10%
4 2018-01-08 273.309998 274.100006 272.980011 273.920013 246.962494 57319200.0 161.919998 162.630005 161.860001 ... 23159100.0 154.729996 155.270004 153.500000 155.029999 143.033173 18457300.0 NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1582 2024-04-15 515.130005 515.299988 503.579987 504.450012 504.450012 92101400.0 442.059998 442.149994 430.209991 ... 63453600.0 199.369995 200.229996 194.979996 195.779999 195.779999 41119300.0 NaN NaN NaN
1583 2024-04-16 504.940002 506.500000 502.209991 503.529999 503.529999 73484000.0 430.899994 433.760010 429.700012 ... 47619000.0 194.410004 196.240005 193.360001 195.059998 195.059998 43267500.0 NaN NaN NaN
1584 2024-04-17 506.049988 506.220001 499.119995 500.549988 500.549988 75910300.0 433.100006 433.119995 424.899994 ... 56880500.0 196.470001 196.619995 192.990005 193.000000 193.000000 38589500.0 NaN NaN NaN
1585 2024-04-18 501.980011 504.130005 498.559998 499.519989 499.519989 74548100.0 426.489990 428.239990 422.829987 ... 46549400.0 193.699997 195.660004 192.149994 192.839996 192.839996 40238200.0 NaN NaN NaN
1586 2024-04-19 499.440002 500.459991 493.859985 495.160004 495.160004 102129100.0 422.220001 422.750000 413.070007 ... 75136600.0 191.940002 194.389999 191.339996 193.139999 193.139999 42499200.0 NaN NaN NaN

1587 rows × 22 columns

In [13]:
# Create a new column 'Announcement_Day' based on the criteria provided
data['Announcement_Day'] = data[['unemployment_Actual', 'unemployment_Forecast', 'unemployment_Previous']].notna().all(axis=1)

# Check the new column and the first few rows to verify
data[['Date', 'unemployment_Actual', 'unemployment_Forecast', 'unemployment_Previous', 'Announcement_Day']].head()
Out[13]:
Date unemployment_Actual unemployment_Forecast unemployment_Previous Announcement_Day
0 2018-01-02 NaN NaN NaN False
1 2018-01-03 NaN NaN NaN False
2 2018-01-04 NaN NaN NaN False
3 2018-01-05 4.10% 4.10% 4.10% True
4 2018-01-08 NaN NaN NaN False
In [14]:
# Convert 'Date' to datetime for easier manipulation
data['Date'] = pd.to_datetime(data['Date'])

# Fill NA values for the unemployment columns by forward filling (using the last known value)
# This assumes the NA should be filled with the most recent available data
for column in ['unemployment_Actual', 'unemployment_Forecast', 'unemployment_Previous']:
    data[column] = data[column].fillna(method='ffill')

# Check the result
data[['Date', 'unemployment_Actual', 'unemployment_Forecast', 'unemployment_Previous']].head(10)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\3161082899.py:7: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  data[column] = data[column].fillna(method='ffill')
Out[14]:
Date unemployment_Actual unemployment_Forecast unemployment_Previous
0 2018-01-02 NaN NaN NaN
1 2018-01-03 NaN NaN NaN
2 2018-01-04 NaN NaN NaN
3 2018-01-05 4.10% 4.10% 4.10%
4 2018-01-08 4.10% 4.10% 4.10%
5 2018-01-09 4.10% 4.10% 4.10%
6 2018-01-10 4.10% 4.10% 4.10%
7 2018-01-11 4.10% 4.10% 4.10%
8 2018-01-12 4.10% 4.10% 4.10%
9 2018-01-16 4.10% 4.10% 4.10%
In [15]:
data.to_csv('project_data.csv')
In [ ]:
 
In [47]:
# Convert unemployment rate columns from strings to floats and handle percentages
for column in ['Actual', 'Forecast', 'Previous']:
    unemployment[column] = unemployment[column].str.rstrip('%').astype(float) / 100

# Check the conversion results
print("Unemployment Data - Converted:")
display(unemployment.head())
Unemployment Data - Converted:
Date unemployment_Actual unemployment_Forecast unemployment_Previous
0 2024-04-05 0.038 0.039 0.039
1 2024-03-08 0.039 0.037 0.037
2 2024-02-02 0.037 0.038 0.037
3 2024-01-05 0.037 0.038 0.037
4 2023-12-08 0.037 0.039 0.039
In [54]:
import matplotlib.pyplot as plt

# Plotting the time series of the adjusted close prices for SPY, QQQ, IWM
plt.figure(figsize=(14, 7))
plt.plot(SPY['Date'], SPY['Adj Close'], label='SPY', color='blue')
plt.plot(QQQ['Date'], QQQ['Adj Close'], label='QQQ', color='red')
plt.plot(IWM['Date'], IWM['Adj Close'], label='IWM', color='green')
plt.title('Adjusted Close Prices Over Time (2018-2023)')
plt.xlabel('Date')
plt.ylabel('Adjusted Close Price')
plt.legend()
plt.grid(True)
plt.show()

# Plotting the unemployment rate over time
plt.figure(figsize=(14, 7))
plt.plot(unemployment['Date'], unemployment['Actual'], label='Actual Unemployment Rate', marker='o', linestyle='-', color='purple')
plt.title('Unemployment Rate Over Time (2018-2023)')
plt.xlabel('Date')
plt.ylabel('Unemployment Rate (%)')
plt.legend()
plt.grid(True)
plt.show()
In [56]:
data['unemployment_Actual'].fillna(method='ffill', inplace=True)
data['unemployment_Forecast'].fillna(method='ffill', inplace=True)
data['unemployment_Previous'].fillna(method='ffill', inplace=True)
data
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:1: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  data['unemployment_Actual'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:1: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  data['unemployment_Actual'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:2: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  data['unemployment_Forecast'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:2: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  data['unemployment_Forecast'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:3: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  data['unemployment_Previous'].fillna(method='ffill', inplace=True)
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_24276\1042633661.py:3: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  data['unemployment_Previous'].fillna(method='ffill', inplace=True)
Out[56]:
Date SPY_Open SPY_High SPY_Low SPY_Close SPY_Adj Close SPY_Volume QQQ_Open QQQ_High QQQ_Low ... QQQ_Volume IWM_Open IWM_High IWM_Low IWM_Close IWM_Adj Close IWM_Volume unemployment_Actual unemployment_Forecast unemployment_Previous
0 2018-01-02 267.839996 268.809998 267.399994 268.769989 242.319351 86655700.0 156.559998 158.529999 156.169998 ... 32573300.0 153.199997 153.970001 152.460007 153.899994 141.990631 20489600.0 NaN NaN NaN
1 2018-01-03 268.959991 270.640015 268.959991 270.470001 243.852097 90070400.0 158.639999 160.169998 158.610001 ... 29383600.0 153.869995 154.460007 153.520004 154.059998 142.138260 21836600.0 NaN NaN NaN
2 2018-01-04 271.200012 272.160004 270.540009 271.609985 244.879929 80636400.0 160.580002 160.789993 160.080002 ... 24776100.0 154.970001 155.149994 154.020004 154.470001 142.516525 14207100.0 NaN NaN NaN
3 2018-01-05 272.510010 273.559998 271.950012 273.420013 246.511826 83524000.0 161.070007 162.029999 160.770004 ... 26992300.0 154.880005 154.979996 153.940002 154.789993 142.811752 19883900.0 4.10% 4.10% 4.10%
4 2018-01-08 273.309998 274.100006 272.980011 273.920013 246.962494 57319200.0 161.919998 162.630005 161.860001 ... 23159100.0 154.729996 155.270004 153.500000 155.029999 143.033173 18457300.0 4.10% 4.10% 4.10%
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1582 2024-04-15 515.130005 515.299988 503.579987 504.450012 504.450012 92101400.0 442.059998 442.149994 430.209991 ... 63453600.0 199.369995 200.229996 194.979996 195.779999 195.779999 41119300.0 3.80% 3.90% 3.90%
1583 2024-04-16 504.940002 506.500000 502.209991 503.529999 503.529999 73484000.0 430.899994 433.760010 429.700012 ... 47619000.0 194.410004 196.240005 193.360001 195.059998 195.059998 43267500.0 3.80% 3.90% 3.90%
1584 2024-04-17 506.049988 506.220001 499.119995 500.549988 500.549988 75910300.0 433.100006 433.119995 424.899994 ... 56880500.0 196.470001 196.619995 192.990005 193.000000 193.000000 38589500.0 3.80% 3.90% 3.90%
1585 2024-04-18 501.980011 504.130005 498.559998 499.519989 499.519989 74548100.0 426.489990 428.239990 422.829987 ... 46549400.0 193.699997 195.660004 192.149994 192.839996 192.839996 40238200.0 3.80% 3.90% 3.90%
1586 2024-04-19 499.440002 500.459991 493.859985 495.160004 495.160004 102129100.0 422.220001 422.750000 413.070007 ... 75136600.0 191.940002 194.389999 191.339996 193.139999 193.139999 42499200.0 3.80% 3.90% 3.90%

1587 rows × 22 columns

Approach

In [38]:
import pandas as pd

# Load the dataset
file_path = 'project_data.csv'
data = pd.read_csv(file_path)

# Display the first few rows and summary of the dataset
data.head(), data.info(), data.describe(include='all')
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1587 entries, 0 to 1586
Data columns (total 24 columns):
 #   Column                 Non-Null Count  Dtype  
---  ------                 --------------  -----  
 0   Unnamed: 0             1587 non-null   int64  
 1   Date                   1587 non-null   object 
 2   SPY_Open               1585 non-null   float64
 3   SPY_High               1585 non-null   float64
 4   SPY_Low                1585 non-null   float64
 5   SPY_Close              1585 non-null   float64
 6   SPY_Adj Close          1585 non-null   float64
 7   SPY_Volume             1585 non-null   float64
 8   QQQ_Open               1585 non-null   float64
 9   QQQ_High               1585 non-null   float64
 10  QQQ_Low                1585 non-null   float64
 11  QQQ_Close              1585 non-null   float64
 12  QQQ_Adj Close          1585 non-null   float64
 13  QQQ_Volume             1585 non-null   float64
 14  IWM_Open               1585 non-null   float64
 15  IWM_High               1585 non-null   float64
 16  IWM_Low                1585 non-null   float64
 17  IWM_Close              1585 non-null   float64
 18  IWM_Adj Close          1585 non-null   float64
 19  IWM_Volume             1585 non-null   float64
 20  unemployment_Actual    1587 non-null   object 
 21  unemployment_Forecast  1587 non-null   object 
 22  unemployment_Previous  1587 non-null   object 
 23  Announcement_Day       1587 non-null   bool   
dtypes: bool(1), float64(18), int64(1), object(4)
memory usage: 286.8+ KB
Out[38]:
(   Unnamed: 0      Date    SPY_Open    SPY_High     SPY_Low   SPY_Close  \
 0           0  1/2/2018  267.839996  268.809998  267.399994  268.769989   
 1           1  1/3/2018  268.959991  270.640015  268.959991  270.470001   
 2           2  1/4/2018  271.200012  272.160004  270.540009  271.609985   
 3           3  1/5/2018  272.510010  273.559998  271.950012  273.420013   
 4           4  1/8/2018  273.309998  274.100006  272.980011  273.920013   
 
    SPY_Adj Close  SPY_Volume    QQQ_Open    QQQ_High  ...    IWM_Open  \
 0     242.319351  86655700.0  156.559998  158.529999  ...  153.199997   
 1     243.852097  90070400.0  158.639999  160.169998  ...  153.869995   
 2     244.879929  80636400.0  160.580002  160.789993  ...  154.970001   
 3     246.511826  83524000.0  161.070007  162.029999  ...  154.880005   
 4     246.962494  57319200.0  161.919998  162.630005  ...  154.729996   
 
      IWM_High     IWM_Low   IWM_Close  IWM_Adj Close  IWM_Volume  \
 0  153.970001  152.460007  153.899994     141.990631  20489600.0   
 1  154.460007  153.520004  154.059998     142.138260  21836600.0   
 2  155.149994  154.020004  154.470001     142.516525  14207100.0   
 3  154.979996  153.940002  154.789993     142.811752  19883900.0   
 4  155.270004  153.500000  155.029999     143.033173  18457300.0   
 
    unemployment_Actual  unemployment_Forecast  unemployment_Previous  \
 0                4.10%                  4.10%                  4.10%   
 1                4.10%                  4.10%                  4.10%   
 2                4.10%                  4.10%                  4.10%   
 3                4.10%                  4.10%                  4.10%   
 4                4.10%                  4.10%                  4.10%   
 
    Announcement_Day  
 0             False  
 1             False  
 2             False  
 3              True  
 4             False  
 
 [5 rows x 24 columns],
 None,
          Unnamed: 0      Date     SPY_Open     SPY_High      SPY_Low  \
 count   1587.000000      1587  1585.000000  1585.000000  1585.000000   
 unique          NaN      1587          NaN          NaN          NaN   
 top             NaN  1/2/2018          NaN          NaN          NaN   
 freq            NaN         1          NaN          NaN          NaN   
 mean     793.000000       NaN   364.879205   367.065962   362.513539   
 std      458.271753       NaN    73.818972    73.996173    73.614979   
 min        0.000000       NaN   228.190002   229.679993   218.259995   
 25%      396.500000       NaN   290.320007   291.399994   289.010010   
 50%      793.000000       NaN   376.239990   379.230011   372.559998   
 75%     1189.500000       NaN   428.279999   431.410004   425.859985   
 max     1586.000000       NaN   523.830017   524.609985   522.780029   
 
           SPY_Close  SPY_Adj Close    SPY_Volume     QQQ_Open     QQQ_High  \
 count   1585.000000    1585.000000  1.585000e+03  1585.000000  1585.000000   
 unique          NaN            NaN           NaN          NaN          NaN   
 top             NaN            NaN           NaN          NaN          NaN   
 freq            NaN            NaN           NaN          NaN          NaN   
 mean     364.927300     349.216599  8.580845e+07   276.979016   279.181016   
 std       73.846777      79.743937  4.202909e+07    83.555345    84.016570   
 min      222.949997     209.932602  2.027000e+07   145.080002   147.979996   
 25%      290.160004     267.618439  5.960380e+07   187.389999   189.080002   
 50%      376.350006     362.775574  7.604280e+07   285.709991   288.859985   
 75%      428.640015     417.491028  9.806810e+07   349.230011   351.790009   
 max      523.169983     523.169983  3.922207e+08   448.880005   449.339996   
 
         ...     IWM_Open     IWM_High      IWM_Low    IWM_Close  \
 count   ...  1585.000000  1585.000000  1585.000000  1585.000000   
 unique  ...          NaN          NaN          NaN          NaN   
 top     ...          NaN          NaN          NaN          NaN   
 freq    ...          NaN          NaN          NaN          NaN   
 mean    ...   177.134618   178.602296   175.440448   177.064631   
 std     ...    27.757920    27.888682    27.585187    27.733031   
 min     ...    99.660004   102.180000    95.690002    99.900002   
 25%     ...   155.550003   156.529999   154.449997   155.419998   
 50%     ...   172.800003   174.449997   171.100006   172.699997   
 75%     ...   196.889999   198.350006   194.350006   196.279999   
 max     ...   243.740005   244.460007   241.929993   242.559998   
 
         IWM_Adj Close    IWM_Volume  unemployment_Actual  \
 count     1585.000000  1.585000e+03                 1587   
 unique            NaN           NaN                   28   
 top               NaN           NaN                3.70%   
 freq              NaN           NaN                  275   
 mean       170.116161  2.786760e+07                  NaN   
 std         28.761500  1.205075e+07                  NaN   
 min         94.527596  1.200000e+03                  NaN   
 25%        145.704117  1.939910e+07                  NaN   
 50%        169.778244  2.516900e+07                  NaN   
 75%        192.839996  3.347860e+07                  NaN   
 max        234.283310  8.624740e+07                  NaN   
 
         unemployment_Forecast  unemployment_Previous  Announcement_Day  
 count                    1587                   1587              1587  
 unique                     27                     28                 2  
 top                     3.60%                  3.70%             False  
 freq                      292                    268              1511  
 mean                      NaN                    NaN               NaN  
 std                       NaN                    NaN               NaN  
 min                       NaN                    NaN               NaN  
 25%                       NaN                    NaN               NaN  
 50%                       NaN                    NaN               NaN  
 75%                       NaN                    NaN               NaN  
 max                       NaN                    NaN               NaN  
 
 [11 rows x 24 columns])
In [39]:
# Convert 'Date' to datetime format
data['Date'] = pd.to_datetime(data['Date'])

# Convert percentage strings to float values for unemployment columns
percentage_columns = ['unemployment_Actual', 'unemployment_Forecast', 'unemployment_Previous']
for column in percentage_columns:
    data[column] = data[column].str.rstrip('%').astype('float') / 100

# Check for missing values in ETF data
missing_data = data[['SPY_Open', 'SPY_Close', 'QQQ_Open', 'QQQ_Close', 'IWM_Open', 'IWM_Close']].isnull().sum()

missing_data
Out[39]:
SPY_Open     2
SPY_Close    2
QQQ_Open     2
QQQ_Close    2
IWM_Open     2
IWM_Close    2
dtype: int64
In [40]:
# Fill missing values using forward fill method
data.fillna(method='ffill', inplace=True)

# Confirm if all missing values are filled
remaining_missing_data = data[['SPY_Open', 'SPY_Close', 'QQQ_Open', 'QQQ_Close', 'IWM_Open', 'IWM_Close']].isnull().sum()

remaining_missing_data
C:\Users\razerblade 15\AppData\Local\Temp\ipykernel_5888\2438766886.py:2: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.
  data.fillna(method='ffill', inplace=True)
Out[40]:
SPY_Open     0
SPY_Close    0
QQQ_Open     0
QQQ_Close    0
IWM_Open     0
IWM_Close    0
dtype: int64
In [41]:
import numpy as np

# Define the event window and estimation window
event_window = 5
estimation_window = 30

# Identify the indices of the announcement days
announcement_indices = data[data['Announcement_Day']].index

# Function to calculate the normal returns using a simple average method
def calculate_normal_returns(index, stock_column):
    if index < estimation_window:
        return np.nan  # Not enough data to calculate normal return
    estimation_period = data.loc[index-estimation_window:index-1, stock_column]
    return estimation_period.mean()

# Initialize columns for abnormal returns
for stock in ['SPY', 'QQQ', 'IWM']:
    data[f'{stock}_Abnormal_Return'] = np.nan

# Calculate abnormal returns
for index in announcement_indices:
    for stock in ['SPY', 'QQQ', 'IWM']:
        normal_return = calculate_normal_returns(index, f'{stock}_Close')
        if pd.isna(normal_return):
            continue  # Skip if normal return is NaN due to insufficient data
        # Event window: from 2 days before to 2 days after the announcement
        for day_offset in range(-2, 3):
            event_day_index = index + day_offset
            if event_day_index >= 0 and event_day_index < len(data):
                actual_return = data.loc[event_day_index, f'{stock}_Close']
                previous_close = data.loc[event_day_index - 1, f'{stock}_Close']
                if pd.notna(actual_return) and pd.notna(previous_close):
                    daily_return = (actual_return - previous_close) / previous_close
                    abnormal_return = daily_return - normal_return
                    data.loc[event_day_index, f'{stock}_Abnormal_Return'] = abnormal_return

# Check results by displaying a few rows with calculated abnormal returns
data.loc[announcement_indices, ['Date', 'SPY_Abnormal_Return', 'QQQ_Abnormal_Return', 'IWM_Abnormal_Return']].head()
Out[41]:
Date SPY_Abnormal_Return QQQ_Abnormal_Return IWM_Abnormal_Return
3 2018-01-05 NaN NaN NaN
22 2018-02-02 NaN NaN NaN
46 2018-03-09 -272.697595 -165.205572 -152.920018
65 2018-04-06 -269.560617 -165.847689 -154.036280
85 2018-05-04 -264.098054 -160.898694 -153.358851
In [42]:
# Correct and simplify the abnormal return calculation

# Function to calculate daily returns
def calculate_daily_returns(data):
    for stock in ['SPY', 'QQQ', 'IWM']:
        data[f'{stock}_Daily_Return'] = data[f'{stock}_Close'].pct_change()

# Calculate daily returns
calculate_daily_returns(data)

# Function to calculate mean daily returns in the estimation window
def calculate_mean_daily_returns(index, stock):
    if index < estimation_window:
        return np.nan  # Not enough data to calculate normal return
    estimation_period_returns = data.loc[index-estimation_window:index-1, f'{stock}_Daily_Return']
    return estimation_period_returns.mean()

# Correct abnormal return calculations
for index in announcement_indices:
    for stock in ['SPY', 'QQQ', 'IWM']:
        mean_daily_return = calculate_mean_daily_returns(index, stock)
        if pd.isna(mean_daily_return):
            continue  # Skip if normal return is NaN due to insufficient data
        # Event window: from 2 days before to 2 days after the announcement
        for day_offset in range(-2, 3):
            event_day_index = index + day_offset
            if event_day_index >= 0 and event_day_index < len(data):
                daily_return = data.loc[event_day_index, f'{stock}_Daily_Return']
                if pd.notna(daily_return):
                    abnormal_return = daily_return - mean_daily_return
                    data.loc[event_day_index, f'{stock}_Abnormal_Return'] = abnormal_return

# Check results again by displaying a few rows with calculated abnormal returns
data.loc[announcement_indices, ['Date', 'SPY_Abnormal_Return', 'QQQ_Abnormal_Return', 'IWM_Abnormal_Return']].head()
Out[42]:
Date SPY_Abnormal_Return QQQ_Abnormal_Return IWM_Abnormal_Return
3 2018-01-05 NaN NaN NaN
22 2018-02-02 NaN NaN NaN
46 2018-03-09 0.018383 0.019013 0.016438
65 2018-04-06 -0.021816 -0.024301 -0.020282
85 2018-05-04 0.013845 0.019866 0.013126
In [43]:
import matplotlib.pyplot as plt
import seaborn as sns

# Add a column to classify the announcement impact
data['Announcement_Impact'] = data.apply(lambda row: 'Positive' if row['unemployment_Actual'] < row['unemployment_Forecast'] else 'Negative', axis=1)

# Filter data for the event window days around announcements
event_window_days = pd.concat([data.loc[index-2:index+2] for index in announcement_indices if index >= 2 and index+2 < len(data)])

# Plotting
fig, axes = plt.subplots(3, 1, figsize=(14, 18), sharex=True)

for i, stock in enumerate(['SPY', 'QQQ', 'IWM']):
    sns.boxplot(x='Announcement_Impact', y=f'{stock}_Abnormal_Return', data=event_window_days, ax=axes[i])
    axes[i].set_title(f'Abnormal Returns for {stock} Around Unemployment Announcements')
    axes[i].set_xlabel('Impact of Unemployment Announcement')
    axes[i].set_ylabel('Abnormal Return')
    axes[i].axhline(0, color='gray', linestyle='--')  # Add a line at zero for reference

plt.tight_layout()
plt.show()
In [44]:
# Plotting each ETF individually with adjusted focus on the median and interquartile range

# Define function for plotting individual ETF
def plot_etf_abnormal_returns(etf_name):
    fig, ax = plt.subplots(figsize=(8, 6))
    sns.boxplot(x='Announcement_Impact', y=f'{etf_name}_Abnormal_Return', data=event_window_days, ax=ax, showfliers=False)
    ax.set_title(f'Focused Abnormal Returns for {etf_name}')
    ax.set_xlabel('Impact of Unemployment Announcement')
    ax.set_ylabel('Abnormal Return')
    ax.axhline(0, color='gray', linestyle='--')  # Add a line at zero for reference
    
    # Determine range for y-axis based on interquartile range
    quartiles = event_window_days[f'{etf_name}_Abnormal_Return'].quantile([0.25, 0.75]).values
    iqr = quartiles[1] - quartiles[0]
    lower_bound = quartiles[0] - 1.5 * iqr
    upper_bound = quartiles[1] + 1.5 * iqr
    ax.set_ylim(lower_bound, upper_bound)
    
    plt.tight_layout()
    plt.show()

# Plot each ETF individually
plot_etf_abnormal_returns('SPY')
plot_etf_abnormal_returns('QQQ')
plot_etf_abnormal_returns('IWM')
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